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--- |
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license: mit |
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base_model: gpt2 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- sst |
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model-index: |
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- name: sst-gpt2 |
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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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# sst-gpt2 |
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This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on the sst dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0218 |
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- Mse: 0.0218 |
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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: 16 |
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- eval_batch_size: 32 |
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- seed: 42 |
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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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- num_epochs: 20 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Mse | |
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|:-------------:|:-----:|:-----:|:---------------:|:------:| |
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| 0.2144 | 1.0 | 534 | 0.0300 | 0.0301 | |
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| 0.0251 | 2.0 | 1068 | 0.0249 | 0.0250 | |
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| 0.0181 | 3.0 | 1602 | 0.0230 | 0.0230 | |
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| 0.0134 | 4.0 | 2136 | 0.0244 | 0.0244 | |
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| 0.0096 | 5.0 | 2670 | 0.0228 | 0.0228 | |
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| 0.0077 | 6.0 | 3204 | 0.0227 | 0.0227 | |
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| 0.0062 | 7.0 | 3738 | 0.0227 | 0.0227 | |
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| 0.0052 | 8.0 | 4272 | 0.0229 | 0.0229 | |
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| 0.0044 | 9.0 | 4806 | 0.0227 | 0.0226 | |
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| 0.0038 | 10.0 | 5340 | 0.0240 | 0.0240 | |
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| 0.0034 | 11.0 | 5874 | 0.0221 | 0.0221 | |
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| 0.0029 | 12.0 | 6408 | 0.0220 | 0.0220 | |
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| 0.0026 | 13.0 | 6942 | 0.0229 | 0.0229 | |
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| 0.0024 | 14.0 | 7476 | 0.0217 | 0.0217 | |
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| 0.002 | 15.0 | 8010 | 0.0225 | 0.0225 | |
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| 0.0018 | 16.0 | 8544 | 0.0222 | 0.0222 | |
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| 0.0016 | 17.0 | 9078 | 0.0217 | 0.0217 | |
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| 0.0015 | 18.0 | 9612 | 0.0218 | 0.0218 | |
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| 0.0014 | 19.0 | 10146 | 0.0217 | 0.0217 | |
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| 0.0013 | 20.0 | 10680 | 0.0218 | 0.0218 | |
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### Framework versions |
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- Transformers 4.37.0 |
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- Pytorch 1.13.1+cu117 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.2 |
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