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--- |
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library_name: transformers |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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- bleu |
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model-index: |
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- name: rotating-head-gp-gpt2-medium-wikitext |
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results: [] |
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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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# rotating-head-gp-gpt2-medium-wikitext |
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This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.1985 |
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- Accuracy: 0.4196 |
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- Perplexity: 24.4954 |
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- Bleu: 0.1339 |
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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: 0.0001 |
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- train_batch_size: 64 |
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- eval_batch_size: 64 |
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- seed: 42 |
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- optimizer: Use OptimizerNames.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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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Perplexity | Bleu | |
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|:-------------:|:------:|:----:|:---------------:|:--------:|:----------:|:------:| |
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| 5.9062 | 0.2806 | 500 | 5.7470 | 0.2234 | 313.2463 | 0.0493 | |
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| 4.8598 | 0.5612 | 1000 | 4.7428 | 0.2811 | 114.7554 | 0.0698 | |
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| 4.3025 | 0.8418 | 1500 | 4.2329 | 0.3170 | 68.9191 | 0.0834 | |
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| 3.9635 | 1.1223 | 2000 | 3.9291 | 0.3454 | 50.8590 | 0.0932 | |
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| 3.7769 | 1.4029 | 2500 | 3.7427 | 0.3636 | 42.2098 | 0.1020 | |
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| 3.6738 | 1.6835 | 3000 | 3.6225 | 0.3754 | 37.4295 | 0.1066 | |
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| 3.5744 | 1.9641 | 3500 | 3.5325 | 0.3845 | 34.2102 | 0.1118 | |
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| 3.456 | 2.2447 | 4000 | 3.4704 | 0.3902 | 32.1497 | 0.1139 | |
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| 3.3972 | 2.5253 | 4500 | 3.4190 | 0.3955 | 30.5384 | 0.1230 | |
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| 3.3654 | 2.8058 | 5000 | 3.3686 | 0.4007 | 29.0392 | 0.1230 | |
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| 3.247 | 3.0864 | 5500 | 3.3328 | 0.4043 | 28.0168 | 0.1247 | |
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| 3.2403 | 3.3670 | 6000 | 3.2985 | 0.4083 | 27.0714 | 0.1298 | |
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| 3.2167 | 3.6476 | 6500 | 3.2693 | 0.4112 | 26.2922 | 0.1288 | |
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| 3.1903 | 3.9282 | 7000 | 3.2456 | 0.4134 | 25.6768 | 0.1305 | |
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| 3.1212 | 4.2088 | 7500 | 3.2262 | 0.4161 | 25.1831 | 0.1325 | |
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| 3.0816 | 4.4893 | 8000 | 3.2128 | 0.4176 | 24.8480 | 0.1307 | |
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| 3.0917 | 4.7699 | 8500 | 3.1985 | 0.4196 | 24.4954 | 0.1339 | |
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### Framework versions |
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- Transformers 4.49.0 |
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- Pytorch 2.6.0+cu124 |
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- Datasets 3.3.2 |
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- Tokenizers 0.21.0 |
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