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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_yem_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_yem_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: 0.0534 |
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- Bleu: 0.0428 |
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- Rouge1: 0.3139 |
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- Rouge2: 0.1104 |
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- Rougel: 0.3097 |
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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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| 5.8224 | 1.0 | 153 | 0.1129 | 0.0039 | 0.0712 | 0.0029 | 0.0695 | |
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| 0.1108 | 2.0 | 306 | 0.0691 | 0.0 | 0.0951 | 0.0078 | 0.0932 | |
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| 0.0775 | 3.0 | 459 | 0.0628 | 0.0067 | 0.1291 | 0.0157 | 0.1286 | |
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| 0.0678 | 4.0 | 612 | 0.0592 | 0.0086 | 0.1524 | 0.0273 | 0.1492 | |
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| 0.0603 | 5.0 | 765 | 0.0566 | 0.0162 | 0.1919 | 0.0413 | 0.1883 | |
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| 0.0547 | 6.0 | 918 | 0.0546 | 0.0187 | 0.2239 | 0.0599 | 0.2218 | |
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| 0.0498 | 7.0 | 1071 | 0.0540 | 0.0295 | 0.2684 | 0.0733 | 0.2638 | |
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| 0.0456 | 8.0 | 1224 | 0.0536 | 0.0292 | 0.2884 | 0.0818 | 0.2841 | |
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| 0.0419 | 9.0 | 1377 | 0.0534 | 0.0428 | 0.3139 | 0.1104 | 0.3097 | |
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| 0.0385 | 10.0 | 1530 | 0.0534 | 0.0461 | 0.3255 | 0.1118 | 0.3185 | |
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| 0.0354 | 11.0 | 1683 | 0.0540 | 0.0473 | 0.3358 | 0.1219 | 0.3288 | |
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| 0.0331 | 12.0 | 1836 | 0.0540 | 0.0476 | 0.3483 | 0.1312 | 0.3442 | |
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| 0.0308 | 13.0 | 1989 | 0.0552 | 0.0590 | 0.3599 | 0.1439 | 0.3539 | |
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| 0.0291 | 14.0 | 2142 | 0.0556 | 0.0625 | 0.3737 | 0.1489 | 0.3670 | |
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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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