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detr-resnet_finetuned

Object Detection
Transformers
Safetensors
detr
Generated from Trainer
Inference Endpoints
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+ ---
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+ library_name: transformers
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+ license: apache-2.0
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+ base_model: facebook/detr-resnet-50-dc5
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: detr-resnet_finetuned
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # detr-resnet_finetuned
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+
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+ This model is a fine-tuned version of [facebook/detr-resnet-50-dc5](https://huggingface.co/facebook/detr-resnet-50-dc5) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 3.4647
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+ - Map: 0.0019
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+ - Map 50: 0.0046
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+ - Map 75: 0.001
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+ - Map Small: 0.0034
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+ - Map Medium: 0.0027
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+ - Map Large: 0.0002
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+ - Mar 1: 0.0031
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+ - Mar 10: 0.0114
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+ - Mar 100: 0.0184
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+ - Mar Small: 0.0155
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+ - Mar Medium: 0.0315
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+ - Mar Large: 0.0178
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+ - Map Shirt, blouse: 0.0
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+ - Mar 100 Shirt, blouse: 0.0
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+ - Map Top, t-shirt, sweatshirt: 0.0
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+ - Mar 100 Top, t-shirt, sweatshirt: 0.0
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+ - Map Sweater: 0.0
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+ - Mar 100 Sweater: 0.0
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+ - Map Cardigan: 0.0
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+ - Mar 100 Cardigan: 0.0
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+ - Map Jacket: 0.0
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+ - Mar 100 Jacket: 0.0
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+ - Map Vest: 0.0
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+ - Mar 100 Vest: 0.0
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+ - Map Pants: 0.0
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+ - Mar 100 Pants: 0.0
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+ - Map Shorts: 0.0
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+ - Mar 100 Shorts: 0.0
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+ - Map Skirt: 0.0
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+ - Mar 100 Skirt: 0.0
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+ - Map Coat: 0.0
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+ - Mar 100 Coat: 0.0
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+ - Map Dress: 0.0
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+ - Mar 100 Dress: 0.0
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+ - Map Jumpsuit: 0.0
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+ - Mar 100 Jumpsuit: 0.0
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+ - Map Glasses: 0.0
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+ - Mar 100 Glasses: 0.0
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+ - Map Hat: 0.0
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+ - Mar 100 Hat: 0.0
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+ - Map Headband, head covering, hair accessory: 0.0
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+ - Mar 100 Headband, head covering, hair accessory: 0.0
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+ - Map Tie: 0.0
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+ - Mar 100 Tie: 0.0
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+ - Map Glove: 0.0
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+ - Mar 100 Glove: 0.0
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+ - Map Watch: 0.0
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+ - Mar 100 Watch: 0.0
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+ - Map Belt: 0.0
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+ - Mar 100 Belt: 0.0
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+ - Map Tights, stockings: 0.0
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+ - Mar 100 Tights, stockings: 0.0
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+ - Map Sock: 0.0
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+ - Mar 100 Sock: 0.0
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+ - Map Shoe: 0.0702
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+ - Mar 100 Shoe: 0.4722
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+ - Map Bag, wallet: 0.0
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+ - Mar 100 Bag, wallet: 0.0
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+ - Map Scarf: 0.0
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+ - Mar 100 Scarf: 0.0
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+ - Map Hood: 0.0
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+ - Mar 100 Hood: 0.0
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+ - Map Collar: 0.0
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+ - Mar 100 Collar: 0.0
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+ - Map Lapel: 0.0
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+ - Mar 100 Lapel: 0.0
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+ - Map Epaulette: 0.0
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+ - Mar 100 Epaulette: 0.0
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+ - Map Sleeve: 0.0104
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+ - Mar 100 Sleeve: 0.3179
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+ - Map Pocket: 0.0
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+ - Mar 100 Pocket: 0.0
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+ - Map Neckline: 0.0
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+ - Mar 100 Neckline: 0.0
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+ - Map Buckle: 0.0
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+ - Mar 100 Buckle: 0.0
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+ - Map Zipper: 0.0
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+ - Mar 100 Zipper: 0.0
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+ - Map Applique: 0.0
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+ - Mar 100 Applique: 0.0
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+ - Map Bead: 0.0
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+ - Mar 100 Bead: 0.0
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+ - Map Bow: 0.0
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+ - Mar 100 Bow: 0.0
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+ - Map Flower: 0.0
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+ - Mar 100 Flower: 0.0
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+ - Map Fringe: 0.0
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+ - Mar 100 Fringe: 0.0
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+ - Map Ribbon: 0.0
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+ - Mar 100 Ribbon: 0.0
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+ - Map Rivet: 0.0
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+ - Mar 100 Rivet: 0.0
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+ - Map Ruffle: 0.0
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+ - Mar 100 Ruffle: 0.0
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+ - Map Sequin: 0.0
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+ - Mar 100 Sequin: 0.0
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+ - Map Tassel: 0.0
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+ - Mar 100 Tassel: 0.0
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 1e-05
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+ - train_batch_size: 4
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+ - eval_batch_size: 4
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+ - seed: 42
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+ - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: linear
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+ - training_steps: 1000
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Map | Map 50 | Map 75 | Map Small | Map Medium | Map Large | Mar 1 | Mar 10 | Mar 100 | Mar Small | Mar Medium | Mar Large | Map Shirt, blouse | Mar 100 Shirt, blouse | Map Top, t-shirt, sweatshirt | Mar 100 Top, t-shirt, sweatshirt | Map Sweater | Mar 100 Sweater | Map Cardigan | Mar 100 Cardigan | Map Jacket | Mar 100 Jacket | Map Vest | Mar 100 Vest | Map Pants | Mar 100 Pants | Map Shorts | Mar 100 Shorts | Map Skirt | Mar 100 Skirt | Map Coat | Mar 100 Coat | Map Dress | Mar 100 Dress | Map Jumpsuit | Mar 100 Jumpsuit | Map Glasses | Mar 100 Glasses | Map Hat | Mar 100 Hat | Map Headband, head covering, hair accessory | Mar 100 Headband, head covering, hair accessory | Map Tie | Mar 100 Tie | Map Glove | Mar 100 Glove | Map Watch | Mar 100 Watch | Map Belt | Mar 100 Belt | Map Leg warmer | Mar 100 Leg warmer | Map Tights, stockings | Mar 100 Tights, stockings | Map Sock | Mar 100 Sock | Map Shoe | Mar 100 Shoe | Map Bag, wallet | Mar 100 Bag, wallet | Map Scarf | Mar 100 Scarf | Map Hood | Mar 100 Hood | Map Collar | Mar 100 Collar | Map Lapel | Mar 100 Lapel | Map Epaulette | Mar 100 Epaulette | Map Sleeve | Mar 100 Sleeve | Map Pocket | Mar 100 Pocket | Map Neckline | Mar 100 Neckline | Map Buckle | Mar 100 Buckle | Map Zipper | Mar 100 Zipper | Map Applique | Mar 100 Applique | Map Bead | Mar 100 Bead | Map Bow | Mar 100 Bow | Map Flower | Mar 100 Flower | Map Fringe | Mar 100 Fringe | Map Ribbon | Mar 100 Ribbon | Map Rivet | Mar 100 Rivet | Map Ruffle | Mar 100 Ruffle | Map Sequin | Mar 100 Sequin | Map Tassel | Mar 100 Tassel |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:----------:|:---------:|:------:|:------:|:-------:|:---------:|:----------:|:---------:|:-----------------:|:---------------------:|:----------------------------:|:--------------------------------:|:-----------:|:---------------:|:------------:|:----------------:|:----------:|:--------------:|:--------:|:------------:|:---------:|:-------------:|:----------:|:--------------:|:---------:|:-------------:|:--------:|:------------:|:---------:|:-------------:|:------------:|:----------------:|:-----------:|:---------------:|:-------:|:-----------:|:-------------------------------------------:|:-----------------------------------------------:|:-------:|:-----------:|:---------:|:-------------:|:---------:|:-------------:|:--------:|:------------:|:--------------:|:------------------:|:---------------------:|:-------------------------:|:--------:|:------------:|:--------:|:------------:|:---------------:|:-------------------:|:---------:|:-------------:|:--------:|:------------:|:----------:|:--------------:|:---------:|:-------------:|:-------------:|:-----------------:|:----------:|:--------------:|:----------:|:--------------:|:------------:|:----------------:|:----------:|:--------------:|:----------:|:--------------:|:------------:|:----------------:|:--------:|:------------:|:-------:|:-----------:|:----------:|:--------------:|:----------:|:--------------:|:----------:|:--------------:|:---------:|:-------------:|:----------:|:--------------:|:----------:|:--------------:|:----------:|:--------------:|
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+ | 6.2369 | 0.5 | 50 | 5.9988 | 0.0 | 0.0001 | 0.0 | 0.0 | 0.0 | 0.0001 | 0.0006 | 0.0015 | 0.0026 | 0.0 | 0.0 | 0.008 | 0.0 | 0.0 | 0.0008 | 0.1029 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0077 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | -1.0 | -1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | 5.0623 | 1.0 | 100 | 5.2277 | 0.0 | 0.0001 | 0.0 | 0.0 | 0.0 | 0.0003 | 0.0008 | 0.0036 | 0.0045 | 0.0083 | 0.0007 | 0.0119 | 0.0 | 0.0 | 0.0017 | 0.1857 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0038 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0002 | 0.0043 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | 4.7145 | 1.5 | 150 | 4.7585 | 0.0001 | 0.0002 | 0.0 | 0.0 | 0.0 | 0.0003 | 0.0001 | 0.0034 | 0.0065 | 0.0 | 0.0041 | 0.0147 | 0.0 | 0.0 | 0.002 | 0.1943 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0008 | 0.0581 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.025 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | 4.2231 | 2.0 | 200 | 4.3844 | 0.0001 | 0.0004 | 0.0 | 0.0 | 0.0001 | 0.0004 | 0.0006 | 0.0037 | 0.0089 | 0.001 | 0.0068 | 0.0254 | 0.0 | 0.0 | 0.0027 | 0.1486 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0001 | 0.0122 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0023 | 0.1709 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0001 | 0.05 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | 3.9842 | 2.5 | 250 | 4.1418 | 0.0003 | 0.0008 | 0.0001 | 0.0004 | 0.0003 | 0.0008 | 0.0008 | 0.0047 | 0.0102 | 0.0078 | 0.0129 | 0.0231 | 0.0 | 0.0 | 0.0052 | 0.0629 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0036 | 0.1661 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0028 | 0.2103 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | 3.9892 | 3.0 | 300 | 3.9676 | 0.0002 | 0.0006 | 0.0001 | 0.0005 | 0.0005 | 0.0003 | 0.0002 | 0.0035 | 0.0095 | 0.0075 | 0.0155 | 0.0166 | 0.0 | 0.0 | 0.0009 | 0.02 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0057 | 0.2243 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0022 | 0.1624 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | 3.7642 | 3.5 | 350 | 3.8193 | 0.0003 | 0.0008 | 0.0001 | 0.001 | 0.0006 | 0.0002 | 0.0 | 0.0049 | 0.0116 | 0.0108 | 0.0187 | 0.0193 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0093 | 0.2817 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0038 | 0.2179 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | 3.1412 | 4.0 | 400 | 3.7189 | 0.0004 | 0.001 | 0.0002 | 0.0011 | 0.0006 | 0.0002 | 0.0006 | 0.0056 | 0.013 | 0.0145 | 0.0199 | 0.0163 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0126 | 0.3409 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0033 | 0.2171 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | 3.6081 | 4.5 | 450 | 3.6870 | 0.0004 | 0.0012 | 0.0002 | 0.0013 | 0.0009 | 0.0002 | 0.0007 | 0.0067 | 0.0136 | 0.014 | 0.0213 | 0.0174 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0148 | 0.3617 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0045 | 0.2239 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | 3.5732 | 5.0 | 500 | 3.6267 | 0.0006 | 0.0016 | 0.0004 | 0.0017 | 0.0009 | 0.0002 | 0.0015 | 0.0074 | 0.0151 | 0.0135 | 0.0254 | 0.0178 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0212 | 0.3957 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0045 | 0.2538 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | 3.4112 | 5.5 | 550 | 3.5980 | 0.001 | 0.0023 | 0.0008 | 0.0025 | 0.0012 | 0.0002 | 0.0017 | 0.0084 | 0.0176 | 0.0153 | 0.0296 | 0.0212 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.034 | 0.4609 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0082 | 0.2966 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
160
+ | 2.9663 | 6.0 | 600 | 3.5557 | 0.0012 | 0.0028 | 0.0007 | 0.0029 | 0.0015 | 0.0002 | 0.0023 | 0.0089 | 0.0165 | 0.0155 | 0.0276 | 0.0205 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0479 | 0.4557 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0046 | 0.2538 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
161
+ | 3.7938 | 6.5 | 650 | 3.5449 | 0.0016 | 0.0035 | 0.001 | 0.0031 | 0.0017 | 0.0002 | 0.0021 | 0.009 | 0.017 | 0.0157 | 0.0286 | 0.0201 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0617 | 0.4583 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0057 | 0.2718 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
162
+ | 3.5334 | 7.0 | 700 | 3.5294 | 0.0016 | 0.004 | 0.001 | 0.0034 | 0.0019 | 0.0002 | 0.0022 | 0.0095 | 0.017 | 0.0154 | 0.0291 | 0.0174 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0624 | 0.4652 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0074 | 0.2641 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
163
+ | 3.5248 | 7.5 | 750 | 3.5182 | 0.0016 | 0.004 | 0.001 | 0.0032 | 0.002 | 0.0002 | 0.0022 | 0.0096 | 0.0169 | 0.0154 | 0.029 | 0.0178 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0631 | 0.4461 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0072 | 0.2803 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
164
+ | 3.4728 | 8.0 | 800 | 3.4755 | 0.0018 | 0.0042 | 0.0013 | 0.0035 | 0.0023 | 0.0002 | 0.0025 | 0.0105 | 0.0179 | 0.016 | 0.0302 | 0.0205 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0702 | 0.4643 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.009 | 0.3068 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
165
+ | 3.063 | 8.5 | 850 | 3.4767 | 0.0018 | 0.0042 | 0.0013 | 0.0034 | 0.0024 | 0.0002 | 0.0025 | 0.0108 | 0.0181 | 0.0155 | 0.0307 | 0.0205 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0687 | 0.4704 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0096 | 0.3077 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
166
+ | 3.823 | 9.0 | 900 | 3.4678 | 0.0019 | 0.0045 | 0.0012 | 0.0034 | 0.0027 | 0.0002 | 0.0027 | 0.0112 | 0.0181 | 0.0155 | 0.0309 | 0.0201 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0721 | 0.4739 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0094 | 0.3043 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
167
+ | 3.6443 | 9.5 | 950 | 3.4681 | 0.0019 | 0.0045 | 0.0011 | 0.0032 | 0.0028 | 0.0002 | 0.0028 | 0.0114 | 0.0184 | 0.0153 | 0.0317 | 0.0182 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0694 | 0.4739 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0108 | 0.3188 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
168
+ | 2.8394 | 10.0 | 1000 | 3.4647 | 0.0019 | 0.0046 | 0.001 | 0.0034 | 0.0027 | 0.0002 | 0.0031 | 0.0114 | 0.0184 | 0.0155 | 0.0315 | 0.0178 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0702 | 0.4722 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0104 | 0.3179 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
169
+
170
+
171
+ ### Framework versions
172
+
173
+ - Transformers 4.46.2
174
+ - Pytorch 2.5.1+cu121
175
+ - Datasets 3.1.0
176
+ - Tokenizers 0.20.3