---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-a-clp-ls
  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. -->

# whisper-a-clp-ls

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0240
- Wer: 10.0629

## 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: 0.0004
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 132
- num_epochs: 11
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer     |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| No log        | 1.0     | 40   | 0.1713          | 46.9602 |
| No log        | 2.0     | 80   | 0.0920          | 28.3019 |
| 1.2158        | 3.0     | 120  | 0.1828          | 31.2369 |
| 1.2158        | 4.0     | 160  | 0.2743          | 42.3480 |
| 0.1604        | 5.0     | 200  | 0.1326          | 62.8931 |
| 0.1604        | 6.0     | 240  | 0.0734          | 25.7862 |
| 0.1604        | 7.0     | 280  | 0.0510          | 15.7233 |
| 0.0502        | 8.0     | 320  | 0.0262          | 10.4822 |
| 0.0502        | 9.0     | 360  | 0.0320          | 11.9497 |
| 0.0202        | 10.0    | 400  | 0.0229          | 7.1279  |
| 0.0202        | 10.7342 | 429  | 0.0240          | 10.0629 |


### Framework versions

- Transformers 4.47.0.dev0
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0