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--- |
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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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- bleu |
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base_model: openai-community/gpt2 |
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model-index: |
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- name: gpt2-finetuned |
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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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# gpt2-finetuned |
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This model is a fine-tuned version of [openai-community/gpt2](https://huggingface.co/openai-community/gpt2) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.6944 |
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- Bleu: 0.0294 |
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- Bertscore Precision: 0.1536 |
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- Bertscore Recall: 0.1658 |
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- Bertscore F1: 0.1592 |
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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: 3e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 16 |
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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 | Bleu | Bertscore Precision | Bertscore Recall | Bertscore F1 | |
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|:-------------:|:-----:|:------:|:---------------:|:------:|:-------------------:|:----------------:|:------------:| |
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| 4.716 | 1.0 | 5750 | 3.4413 | 0.0112 | 0.1417 | 0.1575 | 0.1489 | |
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| 4.5916 | 2.0 | 11500 | 3.2372 | 0.0119 | 0.1424 | 0.1583 | 0.1496 | |
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| 4.325 | 3.0 | 17250 | 3.0534 | 0.0128 | 0.1430 | 0.1587 | 0.1501 | |
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| 4.1626 | 4.0 | 23000 | 2.9061 | 0.0136 | 0.1433 | 0.1592 | 0.1505 | |
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| 4.0255 | 5.0 | 28750 | 2.7554 | 0.0148 | 0.1438 | 0.1599 | 0.1511 | |
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| 3.862 | 6.0 | 34500 | 2.6185 | 0.0346 | 0.1446 | 0.1605 | 0.1518 | |
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| 3.7367 | 7.0 | 40250 | 2.4945 | 0.0286 | 0.1456 | 0.1611 | 0.1527 | |
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| 3.7907 | 8.0 | 46000 | 2.3799 | 0.0401 | 0.1488 | 0.1617 | 0.1548 | |
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| 3.5181 | 9.0 | 51750 | 2.2704 | 0.0607 | 0.1490 | 0.1623 | 0.1551 | |
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| 3.3377 | 10.0 | 57500 | 2.1710 | 0.0804 | 0.1498 | 0.1627 | 0.1558 | |
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| 3.294 | 11.0 | 63250 | 2.0876 | 0.0221 | 0.1512 | 0.1633 | 0.1568 | |
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| 3.1612 | 12.0 | 69000 | 2.0004 | 0.0234 | 0.1516 | 0.1637 | 0.1572 | |
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| 3.1257 | 13.0 | 74750 | 1.9356 | 0.0244 | 0.1518 | 0.1642 | 0.1575 | |
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| 3.1347 | 14.0 | 80500 | 1.8769 | 0.0257 | 0.1525 | 0.1646 | 0.1581 | |
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| 2.8094 | 15.0 | 86250 | 1.8210 | 0.0268 | 0.1527 | 0.1649 | 0.1584 | |
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| 2.8519 | 16.0 | 92000 | 1.7776 | 0.0275 | 0.1530 | 0.1652 | 0.1587 | |
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| 2.782 | 17.0 | 97750 | 1.7438 | 0.0282 | 0.1532 | 0.1654 | 0.1589 | |
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| 2.9097 | 18.0 | 103500 | 1.7183 | 0.0289 | 0.1535 | 0.1657 | 0.1591 | |
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| 2.881 | 19.0 | 109250 | 1.6999 | 0.0293 | 0.1536 | 0.1658 | 0.1592 | |
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| 2.6302 | 20.0 | 115000 | 1.6944 | 0.0294 | 0.1536 | 0.1658 | 0.1592 | |
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### Framework versions |
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- Transformers 4.40.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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