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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: parallel-mean-bottleneck-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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# parallel-mean-bottleneck-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: 3.1859 |
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- Accuracy: 0.4194 |
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- Perplexity: 24.1889 |
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- Bleu: 0.1461 |
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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 | Accuracy | Bleu | Validation Loss | Perplexity | |
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|:-------------:|:------:|:----:|:--------:|:------:|:---------------:|:----------:| |
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| 6.0432 | 0.2806 | 500 | 0.1909 | 0.0378 | 5.9180 | 371.6605 | |
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| 5.0476 | 0.5612 | 1000 | 0.2633 | 0.0612 | 4.8985 | 134.0910 | |
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| 4.3528 | 0.8418 | 1500 | 0.3182 | 0.0834 | 4.2398 | 69.3933 | |
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| 3.9497 | 1.1223 | 2000 | 0.3520 | 0.1054 | 3.8879 | 48.8078 | |
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| 3.7614 | 1.4029 | 2500 | 0.3674 | 0.1207 | 3.7128 | 40.9670 | |
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| 3.6543 | 1.6835 | 3000 | 0.3780 | 0.1310 | 3.5902 | 36.2404 | |
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| 3.5527 | 1.9641 | 3500 | 0.3864 | 0.1337 | 3.5048 | 33.2757 | |
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| 3.4348 | 2.2447 | 4000 | 0.3923 | 0.1361 | 3.4401 | 31.1898 | |
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| 3.3739 | 2.5253 | 4500 | 3.3868 | 0.3974 | 29.5718 | 0.1419 | |
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| 3.3441 | 2.8058 | 5000 | 3.3419 | 0.4020 | 28.2718 | 0.1394 | |
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| 3.2252 | 3.0864 | 5500 | 3.3067 | 0.4057 | 27.2940 | 0.1432 | |
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| 3.2188 | 3.3670 | 6000 | 3.2775 | 0.4088 | 26.5107 | 0.1421 | |
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| 3.1971 | 3.6476 | 6500 | 3.2502 | 0.4115 | 25.7958 | 0.1426 | |
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| 3.1722 | 3.9282 | 7000 | 3.2266 | 0.4143 | 25.1936 | 0.1446 | |
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| 3.1052 | 4.2088 | 7500 | 3.2103 | 0.4163 | 24.7864 | 0.1433 | |
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| 3.0672 | 4.4893 | 8000 | 3.1967 | 0.4180 | 24.4514 | 0.1438 | |
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| 3.0774 | 4.7699 | 8500 | 3.1859 | 0.4194 | 24.1889 | 0.1461 | |
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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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