wav2GPT2MusiSD3200 / README.md
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---
base_model: ''
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: wav2GPT2MusiSD3200
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# wav2GPT2MusiSD3200
This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8962
- Rouge1: 28.7212
- Rouge2: 7.4616
- Rougel: 21.8892
- Rougelsum: 21.8832
- Gen Len: 46.0
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-06
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
| 1.0361 | 1.0 | 1361 | 0.9081 | 28.7212 | 7.4616 | 21.8892 | 21.8832 | 46.0 |
| 1.0015 | 2.0 | 2722 | 0.9021 | 28.1788 | 7.304 | 21.4695 | 21.4607 | 50.0 |
| 1.0003 | 3.0 | 4083 | 0.8976 | 27.7311 | 6.574 | 21.4759 | 21.4402 | 57.0 |
| 0.9761 | 4.0 | 5444 | 0.8914 | 27.7311 | 6.574 | 21.4759 | 21.4402 | 57.0 |
| 0.9928 | 5.0 | 6805 | 0.8884 | 27.7311 | 6.574 | 21.4759 | 21.4402 | 57.0 |
| 1.013 | 6.0 | 8166 | 0.8858 | 27.7311 | 6.574 | 21.4759 | 21.4402 | 57.0 |
| 1.0476 | 7.0 | 9527 | 0.8852 | 27.7311 | 6.574 | 21.4759 | 21.4402 | 57.0 |
| 1.0649 | 8.0 | 10888 | 0.8847 | 27.7311 | 6.574 | 21.4759 | 21.4402 | 57.0 |
| 1.1224 | 9.0 | 12249 | 0.8888 | 29.7298 | 7.2318 | 22.3598 | 22.3739 | 56.0 |
| 1.1818 | 10.0 | 13610 | 0.8949 | 29.7298 | 7.2318 | 22.3598 | 22.3739 | 56.0 |
| 1.1832 | 11.0 | 14971 | 0.8981 | 30.1982 | 7.2766 | 22.0853 | 22.118 | 59.0 |
| 1.1878 | 12.0 | 16332 | 0.8987 | 29.7298 | 7.2318 | 22.3598 | 22.3739 | 56.0 |
| 1.1833 | 13.0 | 17693 | 0.8983 | 29.7298 | 7.2318 | 22.3598 | 22.3739 | 56.0 |
| 1.1772 | 14.0 | 19054 | 0.8980 | 29.7298 | 7.2318 | 22.3598 | 22.3739 | 56.0 |
| 1.1723 | 15.0 | 20415 | 0.8974 | 28.7212 | 7.4616 | 21.8892 | 21.8832 | 46.0 |
| 1.1778 | 16.0 | 21776 | 0.8972 | 28.7212 | 7.4616 | 21.8892 | 21.8832 | 46.0 |
| 1.1707 | 17.0 | 23137 | 0.8968 | 28.7212 | 7.4616 | 21.8892 | 21.8832 | 46.0 |
| 1.1767 | 18.0 | 24498 | 0.8964 | 28.7212 | 7.4616 | 21.8892 | 21.8832 | 46.0 |
| 1.17 | 19.0 | 25859 | 0.8962 | 28.7212 | 7.4616 | 21.8892 | 21.8832 | 46.0 |
| 1.1737 | 20.0 | 27220 | 0.8962 | 28.7212 | 7.4616 | 21.8892 | 21.8832 | 46.0 |
### Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.2
- Tokenizers 0.13.3