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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: 1.4619
- Rouge1: 19.2446
- Rouge2: 2.6708
- Rougel: 17.8027
- Rougelsum: 17.766
- Gen Len: 76.0
## 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: 5e-05
- 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: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
| 2.7069 | 1.0 | 959 | 2.5357 | 18.3668 | 2.1635 | 17.0926 | 17.0433 | 82.0 |
| 2.2934 | 2.0 | 1918 | 2.3074 | 17.0518 | 2.1435 | 16.0006 | 15.9772 | 70.0 |
| 2.1363 | 3.0 | 2877 | 2.1253 | 17.2075 | 2.008 | 16.8224 | 16.7772 | 46.0 |
| 1.9919 | 4.0 | 3836 | 1.9537 | 17.9258 | 2.0952 | 16.7574 | 16.6999 | 88.0 |
| 1.8915 | 5.0 | 4795 | 1.8144 | 17.2075 | 2.008 | 16.8224 | 16.7772 | 46.0 |
| 1.8069 | 6.0 | 5754 | 1.6979 | 15.9274 | 2.3889 | 15.2764 | 15.2325 | 64.0 |
| 1.7355 | 7.0 | 6713 | 1.5992 | 19.2446 | 2.6708 | 17.8027 | 17.766 | 76.0 |
| 1.6694 | 8.0 | 7672 | 1.5291 | 19.2446 | 2.6708 | 17.8027 | 17.766 | 76.0 |
| 1.6216 | 9.0 | 8631 | 1.4830 | 19.2446 | 2.6708 | 17.8027 | 17.766 | 76.0 |
| 1.5901 | 10.0 | 9590 | 1.4619 | 19.2446 | 2.6708 | 17.8027 | 17.766 | 76.0 |
### Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.2
- Tokenizers 0.13.3
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