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

# mina

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: 0.3404
- Wer: 0.2722

## 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: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.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: 50
- training_steps: 12000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 0.7658        | 0.3040 | 500  | 0.4899          | 3.0318 |
| 0.4325        | 0.6079 | 1000 | 0.4118          | 1.6752 |
| 0.379         | 0.9119 | 1500 | 0.3764          | 2.0571 |
| 0.2677        | 1.2158 | 2000 | 0.3626          | 1.5884 |
| 0.2349        | 1.5198 | 2500 | 0.3496          | 0.3929 |
| 0.2304        | 1.8237 | 3000 | 0.3383          | 0.4325 |
| 0.1852        | 2.1277 | 3500 | 0.3402          | 0.2619 |
| 0.1351        | 2.4316 | 4000 | 0.3372          | 0.4407 |
| 0.1352        | 2.7356 | 4500 | 0.3346          | 0.2663 |
| 0.126         | 3.0395 | 5000 | 0.3404          | 0.2722 |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.4.0+cu121
- Datasets 3.6.0
- Tokenizers 0.20.3