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--- |
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base_model: aubmindlab/aragpt2-base |
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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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- rouge |
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model-index: |
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- name: res_nw_dj_aragpt2-base |
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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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# res_nw_dj_aragpt2-base |
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This model is a fine-tuned version of [aubmindlab/aragpt2-base](https://huggingface.co/aubmindlab/aragpt2-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0752 |
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- Bleu: 0.0928 |
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- Rouge1: 0.4343 |
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- Rouge2: 0.2043 |
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- Rougel: 0.4304 |
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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: 8 |
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- eval_batch_size: 8 |
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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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- lr_scheduler_warmup_steps: 500 |
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- num_epochs: 20.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Bleu | Rouge1 | Rouge2 | Rougel | |
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|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:------:| |
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| 0.435 | 1.0 | 2679 | 0.0899 | 0.0225 | 0.2697 | 0.0681 | 0.2649 | |
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| 0.0908 | 2.0 | 5358 | 0.0822 | 0.0495 | 0.3438 | 0.1233 | 0.3394 | |
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| 0.0808 | 3.0 | 8037 | 0.0786 | 0.0670 | 0.3835 | 0.1582 | 0.3790 | |
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| 0.0738 | 4.0 | 10716 | 0.0765 | 0.0782 | 0.4066 | 0.1798 | 0.4025 | |
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| 0.0681 | 5.0 | 13395 | 0.0756 | 0.0880 | 0.4242 | 0.1964 | 0.4204 | |
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| 0.0632 | 6.0 | 16074 | 0.0752 | 0.0928 | 0.4343 | 0.2043 | 0.4304 | |
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| 0.059 | 7.0 | 18753 | 0.0755 | 0.0996 | 0.4439 | 0.2152 | 0.4401 | |
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| 0.0552 | 8.0 | 21432 | 0.0761 | 0.1015 | 0.4500 | 0.2217 | 0.4463 | |
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| 0.0517 | 9.0 | 24111 | 0.0766 | 0.1050 | 0.4527 | 0.2250 | 0.4489 | |
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| 0.0486 | 10.0 | 26790 | 0.0784 | 0.1093 | 0.4612 | 0.2338 | 0.4578 | |
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| 0.0458 | 11.0 | 29469 | 0.0798 | 0.1112 | 0.4634 | 0.2356 | 0.4600 | |
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### Framework versions |
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- Transformers 4.45.0.dev0 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.19.2 |
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- Tokenizers 0.19.1 |
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