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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-lr-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-lr-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: 3.2045 |
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- Accuracy: 0.4189 |
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- Perplexity: 24.6437 |
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- Bleu: 0.1335 |
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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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| 5.9064 | 0.2806 | 500 | 5.7488 | 0.2222 | 313.8089 | 0.0490 | |
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| 4.8623 | 0.5612 | 1000 | 4.7435 | 0.2805 | 114.8386 | 0.0709 | |
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| 4.3005 | 0.8418 | 1500 | 4.2307 | 0.3177 | 68.7669 | 0.0831 | |
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| 3.9583 | 1.1223 | 2000 | 3.9262 | 0.3464 | 50.7124 | 0.0916 | |
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| 3.7778 | 1.4029 | 2500 | 3.7522 | 0.3627 | 42.6128 | 0.1011 | |
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| 3.6805 | 1.6835 | 3000 | 3.6366 | 0.3738 | 37.9607 | 0.1052 | |
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| 3.5792 | 1.9641 | 3500 | 3.5434 | 0.3833 | 34.5829 | 0.1103 | |
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| 3.4655 | 2.2447 | 4000 | 3.4749 | 0.3900 | 32.2934 | 0.1168 | |
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| 3.4063 | 2.5253 | 4500 | 3.4235 | 0.3950 | 30.6766 | 0.1217 | |
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| 3.376 | 2.8058 | 5000 | 3.3767 | 0.4000 | 29.2745 | 0.1242 | |
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| 3.2591 | 3.0864 | 5500 | 3.3395 | 0.4039 | 28.2042 | 0.1258 | |
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| 3.2488 | 3.3670 | 6000 | 3.3072 | 0.4070 | 27.3098 | 0.1278 | |
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| 3.2244 | 3.6476 | 6500 | 3.2740 | 0.4109 | 26.4161 | 0.1309 | |
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| 3.1981 | 3.9282 | 7000 | 3.2526 | 0.4128 | 25.8571 | 0.1290 | |
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| 3.1294 | 4.2088 | 7500 | 3.2318 | 0.4156 | 25.3256 | 0.1293 | |
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| 3.0899 | 4.4893 | 8000 | 3.2180 | 0.4169 | 24.9787 | 0.1296 | |
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| 3.0993 | 4.7699 | 8500 | 3.2045 | 0.4189 | 24.6437 | 0.1335 | |
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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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