LILT-id-warmupv0.2
This model is a fine-tuned version of nielsr/lilt-xlm-roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4560
- Precision: 0.9156
- Recall: 0.9022
- F1: 0.9089
- Accuracy: 0.9499
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 2
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 30
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
No log | 2.4390 | 200 | 0.3327 | 0.8649 | 0.8142 | 0.8388 | 0.9063 |
No log | 4.8780 | 400 | 0.2834 | 0.8866 | 0.8606 | 0.8734 | 0.9305 |
0.5668 | 7.3171 | 600 | 0.3369 | 0.8825 | 0.8631 | 0.8727 | 0.9273 |
0.5668 | 9.7561 | 800 | 0.3568 | 0.8905 | 0.8753 | 0.8829 | 0.9321 |
0.1227 | 12.1951 | 1000 | 0.4180 | 0.8881 | 0.8729 | 0.8804 | 0.9354 |
0.1227 | 14.6341 | 1200 | 0.4567 | 0.8845 | 0.8802 | 0.8824 | 0.9321 |
0.1227 | 17.0732 | 1400 | 0.4374 | 0.9037 | 0.8949 | 0.8993 | 0.9418 |
0.0219 | 19.5122 | 1600 | 0.4580 | 0.9042 | 0.8998 | 0.9020 | 0.9435 |
0.0219 | 21.9512 | 1800 | 0.4570 | 0.9037 | 0.8949 | 0.8993 | 0.9418 |
0.0016 | 24.3902 | 2000 | 0.4560 | 0.9156 | 0.9022 | 0.9089 | 0.9499 |
0.0016 | 26.8293 | 2200 | 0.4563 | 0.9059 | 0.8949 | 0.9004 | 0.9435 |
0.0016 | 29.2683 | 2400 | 0.4642 | 0.9057 | 0.8924 | 0.8990 | 0.9418 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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Model tree for AAmeni/LILT-id-warmupv0.2
Base model
nielsr/lilt-xlm-roberta-base
Finetuned
this model