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

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: 0.2483
- Wer: 21.2742

## 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: 40
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer      |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| No log        | 1.7009  | 100  | 0.4217          | 32.9920  |
| 0.9886        | 3.3932  | 200  | 0.3015          | 275.9954 |
| 0.9886        | 5.0855  | 300  | 0.2714          | 67.1217  |
| 0.2263        | 6.7863  | 400  | 0.2278          | 34.1297  |
| 0.2263        | 8.4786  | 500  | 0.2648          | 314.3345 |
| 0.1309        | 10.1709 | 600  | 0.2952          | 132.0819 |
| 0.1309        | 11.8718 | 700  | 0.2093          | 131.0580 |
| 0.0924        | 13.5641 | 800  | 0.3086          | 161.3197 |
| 0.0924        | 15.2564 | 900  | 0.2621          | 30.9443  |
| 0.0739        | 16.9573 | 1000 | 0.2176          | 30.0341  |
| 0.0739        | 18.6496 | 1100 | 0.2371          | 33.9022  |
| 0.0433        | 20.3419 | 1200 | 0.2281          | 33.9022  |
| 0.0433        | 22.0342 | 1300 | 0.2411          | 33.1058  |
| 0.0249        | 23.7350 | 1400 | 0.2423          | 28.6689  |
| 0.0249        | 25.4274 | 1500 | 0.2758          | 32.5370  |
| 0.0135        | 27.1197 | 1600 | 0.2588          | 27.8726  |
| 0.0135        | 28.8205 | 1700 | 0.2683          | 28.4414  |
| 0.0058        | 30.5128 | 1800 | 0.2603          | 23.4357  |
| 0.0058        | 32.2051 | 1900 | 0.2485          | 20.9329  |
| 0.0003        | 33.9060 | 2000 | 0.2483          | 21.2742  |
| 0.0003        | 35.5983 | 2100 | 0.2482          | 21.2742  |
| 0.0           | 37.2906 | 2200 | 0.2483          | 21.2742  |
| 0.0           | 38.9915 | 2300 | 0.2483          | 21.2742  |


### Framework versions

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