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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: hubert2BertMusic100 |
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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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# hubert2BertMusic100 |
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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: 2.5867 |
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- Rouge1: 36.0915 |
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- Rouge2: 12.101 |
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- Rougel: 26.2764 |
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- Rougelsum: 26.2441 |
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- Gen Len: 25.98 |
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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: 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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| 5.4394 | 1.0 | 983 | 4.7204 | 22.0764 | 4.0274 | 20.3934 | 20.4011 | 61.19 | |
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| 4.8173 | 2.0 | 1966 | 4.2071 | 35.9784 | 15.4735 | 29.1397 | 29.0838 | 34.98 | |
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| 4.2216 | 3.0 | 2949 | 3.6499 | 39.0915 | 15.7932 | 29.828 | 29.8062 | 32.73 | |
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| 3.7867 | 4.0 | 3932 | 3.3676 | 38.2403 | 15.4761 | 28.9872 | 28.9768 | 28.6 | |
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| 3.502 | 5.0 | 4915 | 3.1133 | 41.6179 | 17.8598 | 29.2306 | 29.2435 | 29.2 | |
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| 3.2367 | 6.0 | 5898 | 2.8908 | 36.6649 | 13.4593 | 27.1849 | 27.2161 | 26.21 | |
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| 3.079 | 7.0 | 6881 | 2.7573 | 35.1153 | 11.8019 | 25.6868 | 25.6664 | 23.17 | |
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| 2.9658 | 8.0 | 7864 | 2.6532 | 39.4462 | 13.8979 | 28.2899 | 28.296 | 33.88 | |
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| 2.8801 | 9.0 | 8847 | 2.6063 | 39.2319 | 13.9339 | 28.2368 | 28.265 | 30.96 | |
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| 2.8509 | 10.0 | 9830 | 2.5867 | 36.0915 | 12.101 | 26.2764 | 26.2441 | 25.98 | |
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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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