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--- |
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language: |
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- mn |
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license: mit |
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tags: |
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- generated_from_trainer |
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metrics: |
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- precision |
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- recall |
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- f1 |
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- accuracy |
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model-index: |
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- name: gpt-2-10000 |
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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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# gpt-2-10000 |
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This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2551 |
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- Precision: 0.1523 |
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- Recall: 0.2608 |
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- F1: 0.1923 |
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- Accuracy: 0.9175 |
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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: 2e-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: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
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| 0.4502 | 1.0 | 477 | 0.3178 | 0.1351 | 0.2289 | 0.1699 | 0.8953 | |
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| 0.3283 | 2.0 | 954 | 0.3014 | 0.1227 | 0.2220 | 0.1581 | 0.8985 | |
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| 0.3016 | 3.0 | 1431 | 0.2768 | 0.1441 | 0.2379 | 0.1795 | 0.9077 | |
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| 0.2824 | 4.0 | 1908 | 0.2687 | 0.1442 | 0.2415 | 0.1806 | 0.9103 | |
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| 0.2686 | 5.0 | 2385 | 0.2697 | 0.1374 | 0.2383 | 0.1743 | 0.9086 | |
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| 0.2568 | 6.0 | 2862 | 0.2573 | 0.1450 | 0.2525 | 0.1842 | 0.9140 | |
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| 0.2472 | 7.0 | 3339 | 0.2534 | 0.1492 | 0.2574 | 0.1889 | 0.9166 | |
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| 0.2405 | 8.0 | 3816 | 0.2548 | 0.1413 | 0.2515 | 0.1809 | 0.9153 | |
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| 0.2345 | 9.0 | 4293 | 0.2545 | 0.1489 | 0.2564 | 0.1884 | 0.9163 | |
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| 0.2299 | 10.0 | 4770 | 0.2551 | 0.1523 | 0.2608 | 0.1923 | 0.9175 | |
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### Framework versions |
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- Transformers 4.28.1 |
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- Pytorch 2.0.0+cu118 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.3 |
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