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

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: 0.0267
- Wer: 11.7400

## 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: 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: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer     |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| 3.4117        | 2.5063  | 100  | 0.6501          | 50.3145 |
| 0.1828        | 5.0     | 200  | 0.0349          | 25.3669 |
| 0.0163        | 7.5063  | 300  | 0.0345          | 19.4969 |
| 0.0111        | 10.0    | 400  | 0.0335          | 25.3669 |
| 0.0076        | 12.5063 | 500  | 0.0279          | 14.2558 |
| 0.0074        | 15.0    | 600  | 0.0262          | 12.3690 |
| 0.0064        | 17.5063 | 700  | 0.0260          | 12.1593 |
| 0.0051        | 20.0    | 800  | 0.0262          | 12.1593 |
| 0.0041        | 22.5063 | 900  | 0.0280          | 9.2243  |
| 0.0037        | 25.0    | 1000 | 0.0275          | 11.5304 |
| 0.0029        | 27.5063 | 1100 | 0.0267          | 11.7400 |


### Framework versions

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