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--- |
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base_model: '' |
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tags: |
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- generated_from_trainer |
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metrics: |
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- rouge |
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model-index: |
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- name: hubert2BertMusic200 |
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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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# hubert2BertMusic200 |
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This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.4375 |
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- Rouge1: 29.0195 |
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- Rouge2: 7.3975 |
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- Rougel: 20.4993 |
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- Rougelsum: 20.3634 |
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- Gen Len: 52.81 |
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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: 1e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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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: 10 |
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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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| 1.8641 | 1.0 | 1361 | 1.6566 | 29.2626 | 7.4871 | 20.625 | 20.5664 | 60.57 | |
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| 1.7169 | 2.0 | 2722 | 1.5973 | 26.9521 | 7.8677 | 19.7208 | 19.6278 | 50.38 | |
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| 1.6726 | 3.0 | 4083 | 1.5585 | 30.2177 | 7.3497 | 20.92 | 20.8207 | 60.63 | |
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| 1.628 | 4.0 | 5444 | 1.5186 | 28.2694 | 7.5824 | 19.796 | 19.7173 | 56.45 | |
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| 1.6528 | 5.0 | 6805 | 1.4964 | 27.9623 | 7.8577 | 20.0053 | 19.92 | 52.75 | |
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| 1.6151 | 6.0 | 8166 | 1.4718 | 30.3355 | 7.9194 | 20.9989 | 20.9562 | 55.94 | |
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| 1.6218 | 7.0 | 9527 | 1.4591 | 27.9266 | 7.673 | 20.1116 | 20.0565 | 54.25 | |
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| 1.6252 | 8.0 | 10888 | 1.4481 | 28.8105 | 7.6804 | 20.5785 | 20.4439 | 52.84 | |
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| 1.6551 | 9.0 | 12249 | 1.4407 | 28.4905 | 7.2818 | 20.0679 | 19.9556 | 55.59 | |
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| 1.6986 | 10.0 | 13610 | 1.4375 | 29.0195 | 7.3975 | 20.4993 | 20.3634 | 52.81 | |
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### Framework versions |
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- Transformers 4.31.0 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.14.2 |
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- Tokenizers 0.13.3 |
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