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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_eg_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_eg_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: 0.1032 |
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- Bleu: 0.1405 |
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- Rouge1: 0.4455 |
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- Rouge2: 0.2251 |
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- Rougel: 0.4383 |
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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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| 0.2542 | 1.0 | 7105 | 0.1199 | 0.0729 | 0.3187 | 0.1103 | 0.3094 | |
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| 0.1078 | 2.0 | 14210 | 0.1119 | 0.1044 | 0.3803 | 0.1636 | 0.3720 | |
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| 0.0972 | 3.0 | 21315 | 0.1077 | 0.1222 | 0.4109 | 0.1933 | 0.4033 | |
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| 0.0902 | 4.0 | 28420 | 0.1051 | 0.1312 | 0.4294 | 0.2090 | 0.4223 | |
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| 0.0846 | 5.0 | 35525 | 0.1032 | 0.1405 | 0.4455 | 0.2251 | 0.4383 | |
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| 0.0799 | 6.0 | 42630 | 0.1041 | 0.1454 | 0.4537 | 0.2338 | 0.4466 | |
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| 0.0759 | 7.0 | 49735 | 0.1044 | 0.1494 | 0.4623 | 0.2425 | 0.4553 | |
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| 0.0722 | 8.0 | 56840 | 0.1044 | 0.1527 | 0.4655 | 0.2470 | 0.4587 | |
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| 0.069 | 9.0 | 63945 | 0.1058 | 0.1536 | 0.4689 | 0.2489 | 0.4621 | |
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| 0.066 | 10.0 | 71050 | 0.1062 | 0.1550 | 0.4724 | 0.2523 | 0.4657 | |
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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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