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--- |
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library_name: peft |
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tags: |
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- generated_from_trainer |
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base_model: d0rj/rut5-base-summ |
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metrics: |
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- rouge |
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model-index: |
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- name: summary_about_me |
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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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# summary_about_me |
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This model is a fine-tuned version of [d0rj/rut5-base-summ](https://huggingface.co/d0rj/rut5-base-summ) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.9918 |
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- Rouge1: 0.9677 |
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- Rouge2: 0.8966 |
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- Rougel: 0.9677 |
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- Rougelsum: 0.9677 |
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- Gen Len: 79.0 |
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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: 1 |
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- eval_batch_size: 1 |
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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: 25 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:| |
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| No log | 1.0 | 50 | 1.3458 | 0.0 | 0.0 | 0.0 | 0.0 | 20.0 | |
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| No log | 2.0 | 100 | 1.3283 | 0.0 | 0.0 | 0.0 | 0.0 | 20.0 | |
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| No log | 3.0 | 150 | 1.3000 | 0.0 | 0.0 | 0.0 | 0.0 | 17.0 | |
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| No log | 4.0 | 200 | 1.2688 | 0.0 | 0.0 | 0.0 | 0.0 | 17.0 | |
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| No log | 5.0 | 250 | 1.2354 | 0.0 | 0.0 | 0.0 | 0.0 | 17.0 | |
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| No log | 6.0 | 300 | 1.2041 | 0.0 | 0.0 | 0.0 | 0.0 | 20.0 | |
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| No log | 7.0 | 350 | 1.1791 | 0.0 | 0.0 | 0.0 | 0.0 | 10.0 | |
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| No log | 8.0 | 400 | 1.1403 | 0.0 | 0.0 | 0.0 | 0.0 | 17.0 | |
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| No log | 9.0 | 450 | 1.1153 | 0.0 | 0.0 | 0.0 | 0.0 | 17.0 | |
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| 2.0999 | 10.0 | 500 | 1.0938 | 0.0 | 0.0 | 0.0 | 0.0 | 17.0 | |
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| 2.0999 | 11.0 | 550 | 1.0813 | 0.0 | 0.0 | 0.0 | 0.0 | 17.0 | |
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| 2.0999 | 12.0 | 600 | 1.0607 | 0.1176 | 0.0 | 0.1176 | 0.1176 | 35.0 | |
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| 2.0999 | 13.0 | 650 | 1.0508 | 0.9333 | 0.8571 | 0.9333 | 0.9333 | 44.0 | |
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| 2.0999 | 14.0 | 700 | 1.0386 | 0.9333 | 0.8571 | 0.9333 | 0.9333 | 44.0 | |
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| 2.0999 | 15.0 | 750 | 1.0293 | 0.9333 | 0.8571 | 0.9333 | 0.9333 | 44.0 | |
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| 2.0999 | 16.0 | 800 | 1.0210 | 0.9333 | 0.8571 | 0.9333 | 0.9333 | 44.0 | |
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| 2.0999 | 17.0 | 850 | 1.0151 | 0.9333 | 0.8571 | 0.9333 | 0.9333 | 44.0 | |
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| 2.0999 | 18.0 | 900 | 1.0084 | 0.0 | 0.0 | 0.0 | 0.0 | 10.0 | |
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| 2.0999 | 19.0 | 950 | 1.0039 | 0.9677 | 0.8966 | 0.9677 | 0.9677 | 79.0 | |
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| 1.8806 | 20.0 | 1000 | 0.9999 | 0.9677 | 0.8966 | 0.9677 | 0.9677 | 79.0 | |
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| 1.8806 | 21.0 | 1050 | 0.9963 | 0.9677 | 0.8966 | 0.9677 | 0.9677 | 79.0 | |
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| 1.8806 | 22.0 | 1100 | 0.9943 | 0.9677 | 0.8966 | 0.9677 | 0.9677 | 79.0 | |
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| 1.8806 | 23.0 | 1150 | 0.9932 | 0.9677 | 0.8966 | 0.9677 | 0.9677 | 79.0 | |
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| 1.8806 | 24.0 | 1200 | 0.9925 | 0.9677 | 0.8966 | 0.9677 | 0.9677 | 79.0 | |
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| 1.8806 | 25.0 | 1250 | 0.9918 | 0.9677 | 0.8966 | 0.9677 | 0.9677 | 79.0 | |
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### Framework versions |
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- PEFT 0.11.1 |
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- Transformers 4.41.0 |
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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 |
