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

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 5.1515
- Wer: 1.0004

## 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: 0.0001
- train_batch_size: 1
- eval_batch_size: 8
- seed: 42
- 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: 500
- training_steps: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer    |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 2.1863        | 1.6393  | 500  | 3.5257          | 0.9991 |
| 1.4263        | 3.2787  | 1000 | 4.2011          | 1.0383 |
| 1.1951        | 4.9180  | 1500 | 4.1093          | 0.9934 |
| 0.8698        | 6.5574  | 2000 | 4.3517          | 1.7507 |
| 0.7181        | 8.1967  | 2500 | 4.5794          | 1.2076 |
| 0.718         | 9.8361  | 3000 | 4.6911          | 1.2960 |
| 0.5776        | 11.4754 | 3500 | 4.8927          | 1.0814 |
| 0.624         | 13.1148 | 4000 | 4.9520          | 1.1319 |
| 0.5781        | 14.7541 | 4500 | 5.0590          | 0.9934 |
| 0.5189        | 16.3934 | 5000 | 5.1515          | 1.0004 |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0