---
license: apache-2.0
base_model: openai/whisper-base.en
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: whispherMusic
  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. -->

# whispherMusic

This model is a fine-tuned version of [openai/whisper-base.en](https://huggingface.co/openai/whisper-base.en) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6119
- Rouge1: 44.2768
- Rouge2: 23.1307
- Rougel: 36.7378
- Rougelsum: 36.7159
- Gen Len: 72.18

## 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-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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 2.3982        | 1.0   | 959  | 2.0620          | 26.4298 | 5.9908  | 23.2899 | 23.3213   | 64.6    |
| 1.7265        | 2.0   | 1918 | 1.6701          | 27.8931 | 6.8526  | 24.1834 | 24.1954   | 65.1    |
| 1.4192        | 3.0   | 2877 | 1.3889          | 30.545  | 8.5986  | 26.1328 | 26.1093   | 63.72   |
| 1.215         | 4.0   | 3836 | 1.1685          | 32.7599 | 10.5476 | 27.2588 | 27.2407   | 66.01   |
| 1.0452        | 5.0   | 4795 | 0.9892          | 33.4751 | 11.1674 | 27.5111 | 27.4954   | 65.03   |
| 0.8959        | 6.0   | 5754 | 0.8506          | 35.995  | 13.1211 | 29.6986 | 29.745    | 67.8    |
| 0.7872        | 7.0   | 6713 | 0.7457          | 39.7262 | 16.9675 | 32.8461 | 32.8319   | 70.65   |
| 0.6891        | 8.0   | 7672 | 0.6733          | 41.6536 | 19.7787 | 34.6224 | 34.5889   | 67.49   |
| 0.6223        | 9.0   | 8631 | 0.6272          | 43.4958 | 21.9107 | 36.5012 | 36.4477   | 72.2    |
| 0.5763        | 10.0  | 9590 | 0.6119          | 44.2768 | 23.1307 | 36.7378 | 36.7159   | 72.18   |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.2
- Tokenizers 0.13.3