---
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-25
  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-25

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: 0.0302
- Wer: 8.3857

## 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   | 0.1805          | 27.4633 |
| No log        | 2.0     | 80   | 0.2522          | 54.9266 |
| 1.2203        | 3.0     | 120  | 0.2866          | 59.5388 |
| 1.2203        | 4.0     | 160  | 0.1374          | 43.3962 |
| 0.1533        | 5.0     | 200  | 0.1516          | 46.1216 |
| 0.1533        | 6.0     | 240  | 0.1406          | 53.4591 |
| 0.1533        | 7.0     | 280  | 0.0704          | 17.8197 |
| 0.0561        | 8.0     | 320  | 0.0487          | 15.0943 |
| 0.0561        | 9.0     | 360  | 0.0395          | 11.7400 |
| 0.0225        | 10.0    | 400  | 0.0291          | 6.2893  |
| 0.0225        | 10.7342 | 429  | 0.0302          | 8.3857  |


### Framework versions

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