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: 1.4167
- Rouge1: 46.3177
- Rouge2: 18.1696
- Rougel: 34.6558
- Rougelsum: 34.636
- Gen Len: 40.0
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 2.8481 | 1.0 | 983 | 2.2495 | 34.5797 | 8.9817 | 28.3195 | 28.32 | 28.0 |
| 2.4137 | 2.0 | 1966 | 2.0846 | 36.3928 | 12.5876 | 27.98 | 27.9842 | 21.0 |
| 2.2635 | 3.0 | 2949 | 1.9332 | 35.1245 | 9.6761 | 29.1228 | 29.155 | 27.0 |
| 2.1176 | 4.0 | 3932 | 1.8091 | 34.5774 | 10.3811 | 27.872 | 27.8823 | 21.0 |
| 2.0186 | 5.0 | 4915 | 1.6961 | 31.3649 | 9.5216 | 26.2574 | 26.254 | 38.0 |
| 1.9291 | 6.0 | 5898 | 1.6045 | 39.5512 | 13.1811 | 30.9223 | 30.9325 | 40.0 |
| 1.8468 | 7.0 | 6881 | 1.5318 | 41.6641 | 14.5078 | 31.932 | 31.9302 | 39.0 |
| 1.7885 | 8.0 | 7864 | 1.4718 | 46.3177 | 18.1696 | 34.6558 | 34.636 | 40.0 |
| 1.7379 | 9.0 | 8847 | 1.4323 | 45.3182 | 17.9076 | 33.0305 | 33.0228 | 47.0 |
| 1.6984 | 10.0 | 9830 | 1.4167 | 46.3177 | 18.1696 | 34.6558 | 34.636 | 40.0 |
### Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.2
- Tokenizers 0.13.3