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

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: 0.0723
- Wer: 15.2655

## 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: 15
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer      |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 1.3968        | 0.9217  | 100  | 0.7677          | 512.9794 |
| 0.3388        | 1.8387  | 200  | 0.3331          | 93.3628  |
| 0.2711        | 2.7558  | 300  | 0.2512          | 87.0944  |
| 0.2383        | 3.6728  | 400  | 0.2198          | 87.9056  |
| 0.2096        | 4.5899  | 500  | 0.1971          | 80.3835  |
| 0.2131        | 5.5069  | 600  | 0.1680          | 75.5900  |
| 0.1498        | 6.4240  | 700  | 0.1433          | 56.1209  |
| 0.1152        | 7.3410  | 800  | 0.1094          | 41.0767  |
| 0.0833        | 8.2581  | 900  | 0.1193          | 65.9292  |
| 0.0653        | 9.1751  | 1000 | 0.0728          | 25.1475  |
| 0.0444        | 10.0922 | 1100 | 0.0781          | 24.4100  |
| 0.0383        | 11.0092 | 1200 | 0.0537          | 17.6991  |
| 0.0269        | 11.9309 | 1300 | 0.0658          | 18.0678  |
| 0.0182        | 12.8479 | 1400 | 0.0641          | 19.3215  |
| 0.0128        | 13.7650 | 1500 | 0.0679          | 15.8555  |
| 0.0068        | 14.6820 | 1600 | 0.0723          | 15.2655  |


### Framework versions

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