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README.md
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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: wav2GPT2MusiSD3100
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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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# wav2GPT2MusiSD3100
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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: 1.4161
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- Rouge1: 44.7443
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- Rouge2: 17.1312
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- Rougel: 32.345
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- Rougelsum: 32.3028
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- Gen Len: 48.0
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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: 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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| 2.8472 | 1.0 | 983 | 2.2487 | 34.6108 | 8.988 | 28.3576 | 28.296 | 28.0 |
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| 2.4122 | 2.0 | 1966 | 2.0819 | 32.7125 | 12.0296 | 26.8296 | 26.8069 | 17.0 |
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| 2.2629 | 3.0 | 2949 | 1.9330 | 35.1797 | 9.6539 | 29.1791 | 29.1386 | 27.0 |
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| 2.1172 | 4.0 | 3932 | 1.8069 | 35.1797 | 9.6539 | 29.1791 | 29.1386 | 27.0 |
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| 2.0178 | 5.0 | 4915 | 1.6942 | 31.452 | 9.5377 | 26.3165 | 26.2784 | 38.0 |
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| 1.929 | 6.0 | 5898 | 1.6032 | 40.4263 | 13.1411 | 30.9662 | 30.876 | 41.0 |
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| 1.8463 | 7.0 | 6881 | 1.5313 | 42.0504 | 14.6769 | 32.1858 | 32.11 | 38.0 |
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| 1.7884 | 8.0 | 7864 | 1.4716 | 43.0698 | 14.1014 | 32.5069 | 32.4717 | 38.0 |
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| 1.738 | 9.0 | 8847 | 1.4317 | 44.7769 | 17.0917 | 32.2387 | 32.1911 | 48.0 |
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| 1.6979 | 10.0 | 9830 | 1.4161 | 44.7443 | 17.1312 | 32.345 | 32.3028 | 48.0 |
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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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