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README.md
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This model is a fine-tuned version of [lvwerra/gpt2-imdb](https://huggingface.co/lvwerra/gpt2-imdb) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Rewards/
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- Rewards/
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- Rewards/
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- Logps/
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- Logits/
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## Model description
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| 0.2231 | 1.67 | 4000 | 0.1884 | -2.3281 | -5.6096 | 0.9208 | 3.2815 | -319.7815 | -258.5467 | -45.7720 | -46.8600 |
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| 0.2269 | 1.88 | 4500 | 0.1785 | -2.5145 | -6.0015 | 0.9292 | 3.4871 | -323.7006 | -260.4101 | -45.7220 | -46.8746 |
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| 0.1831 | 2.08 | 5000 | 0.1727 | -2.6850 | -6.2801 | 0.9312 | 3.5951 | -326.4862 | -262.1152 | -45.0514 | -46.1610 |
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| 0.0112 | 2.29 | 5500 | 0.1682 | -2.5613 | -6.0913 | 0.9312 | 3.5300 | -324.5987 | -260.8782 | -45.3410 | -46.5522 |
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| 0.1894 | 2.5 | 6000 | 0.1706 | -2.7334 | -6.3632 | 0.9271 | 3.6298 | -327.3174 | -262.5995 | -45.2020 | -46.4449 |
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| 0.13 | 2.71 | 6500 | 0.1685 | -2.7681 | -6.4203 | 0.9250 | 3.6522 | -327.8886 | -262.9462 | -45.5580 | -46.8017 |
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| 0.2717 | 2.92 | 7000 |
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### Framework versions
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This model is a fine-tuned version of [lvwerra/gpt2-imdb](https://huggingface.co/lvwerra/gpt2-imdb) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Step: 5500
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- Loss: 0.1682
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- Rewards/chosen: -2.5613
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- Rewards/rejected: -6.0913
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- Rewards/accuracies: 0.9312
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- Rewards/margins: 3.5300
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- Logps/rejected: -324.5987
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- Logps/chosen: -260.8782
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- Logits/rejected: -45.3410
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- Logits/chosen: -46.5522
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## Model description
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| 0.2231 | 1.67 | 4000 | 0.1884 | -2.3281 | -5.6096 | 0.9208 | 3.2815 | -319.7815 | -258.5467 | -45.7720 | -46.8600 |
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| 0.2269 | 1.88 | 4500 | 0.1785 | -2.5145 | -6.0015 | 0.9292 | 3.4871 | -323.7006 | -260.4101 | -45.7220 | -46.8746 |
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| 0.1831 | 2.08 | 5000 | 0.1727 | -2.6850 | -6.2801 | 0.9312 | 3.5951 | -326.4862 | -262.1152 | -45.0514 | -46.1610 |
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| 0.0112 | 2.29 | 5500 | **0.1682** | -2.5613 | -6.0913 | 0.9312 | 3.5300 | -324.5987 | -260.8782 | -45.3410 | -46.5522 |
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| 0.1894 | 2.5 | 6000 | 0.1706 | -2.7334 | -6.3632 | 0.9271 | 3.6298 | -327.3174 | -262.5995 | -45.2020 | -46.4449 |
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| 0.13 | 2.71 | 6500 | 0.1685 | -2.7681 | -6.4203 | 0.9250 | 3.6522 | -327.8886 | -262.9462 | -45.5580 | -46.8017 |
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| 0.2717 | 2.92 | 7000 | 0.1683 | -2.7548 | -6.4029 | 0.9271 | 3.6481 | -327.7139 | -262.8134 | -45.7026 | -46.9404 |
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### Framework versions
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