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--- |
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license: mit |
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base_model: roberta-base |
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tags: |
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- generated_from_trainer |
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datasets: |
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- wikitext |
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metrics: |
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- accuracy |
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model-index: |
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- name: mlm |
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results: |
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- task: |
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name: Masked Language Modeling |
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type: fill-mask |
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dataset: |
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name: wikitext wikitext-2-raw-v1 |
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type: wikitext |
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config: wikitext-2-raw-v1 |
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split: validation |
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args: wikitext-2-raw-v1 |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.7255275697753574 |
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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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# mlm |
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This model is a fine-tuned version of [roberta-base](https://huggingface.co./roberta-base) on the wikitext wikitext-2-raw-v1 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.2799 |
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- Accuracy: 0.7255 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 3e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 0 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 32 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| 1.3784 | 1.0 | 150 | 1.2822 | 0.7290 | |
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| 1.3804 | 2.0 | 300 | 1.2755 | 0.7273 | |
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| 1.3586 | 3.0 | 450 | 1.2628 | 0.7288 | |
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### Framework versions |
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- Transformers 4.33.0.dev0 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.13.1 |
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- Tokenizers 0.13.3 |
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