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--- |
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license: mit |
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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: wikitext_roberta-base |
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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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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: 0.7371052344006119 |
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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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# wikitext_roberta-base |
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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: 1.2143 |
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- Accuracy: 0.7371 |
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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: 5e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 16 |
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- total_train_batch_size: 128 |
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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_steps: 50 |
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- num_epochs: 20.0 |
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- mixed_precision_training: Native AMP |
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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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| 1.4175 | 0.99 | 37 | 1.3355 | 0.7194 | |
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| 1.438 | 1.99 | 74 | 1.2953 | 0.7249 | |
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| 1.4363 | 2.99 | 111 | 1.2759 | 0.7276 | |
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| 1.3391 | 3.99 | 148 | 1.2904 | 0.7252 | |
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| 1.3741 | 4.99 | 185 | 1.2621 | 0.7290 | |
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| 1.2771 | 5.99 | 222 | 1.2312 | 0.7353 | |
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| 1.287 | 6.99 | 259 | 1.2542 | 0.7289 | |
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| 1.29 | 7.99 | 296 | 1.2290 | 0.7345 | |
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| 1.2948 | 8.99 | 333 | 1.2537 | 0.7286 | |
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| 1.2741 | 9.99 | 370 | 1.2199 | 0.7354 | |
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| 1.2342 | 10.99 | 407 | 1.2520 | 0.7309 | |
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| 1.2199 | 11.99 | 444 | 1.2738 | 0.7260 | |
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| 1.206 | 12.99 | 481 | 1.2286 | 0.7335 | |
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| 1.221 | 13.99 | 518 | 1.2421 | 0.7327 | |
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| 1.2062 | 14.99 | 555 | 1.2402 | 0.7328 | |
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| 1.2305 | 15.99 | 592 | 1.2473 | 0.7308 | |
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| 1.2426 | 16.99 | 629 | 1.2250 | 0.7318 | |
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| 1.2096 | 17.99 | 666 | 1.2186 | 0.7353 | |
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| 1.1961 | 18.99 | 703 | 1.2214 | 0.7361 | |
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| 1.2136 | 19.99 | 740 | 1.2506 | 0.7311 | |
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### Framework versions |
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- Transformers 4.21.0.dev0 |
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- Pytorch 1.11.0+cu113 |
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- Datasets 2.3.3.dev0 |
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- Tokenizers 0.12.1 |
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