---
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-small-r22-e
  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-small-r22-e

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: 0.2918
- Wer: 21.3875

## 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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 5
- training_steps: 150
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.3822        | 0.09  | 10   | 0.4255          | 23.2826 |
| 0.2636        | 0.18  | 20   | 0.3321          | 22.4196 |
| 0.2037        | 0.27  | 30   | 0.3279          | 23.8071 |
| 0.1943        | 0.36  | 40   | 0.3177          | 22.3858 |
| 0.2203        | 0.45  | 50   | 0.3109          | 22.4873 |
| 0.193         | 0.54  | 60   | 0.3071          | 22.9272 |
| 0.2096        | 0.63  | 70   | 0.2990          | 22.6565 |
| 0.214         | 0.72  | 80   | 0.3029          | 22.4873 |
| 0.2375        | 0.81  | 90   | 0.2927          | 21.7259 |
| 0.2238        | 0.9   | 100  | 0.2918          | 22.4196 |
| 0.2119        | 0.99  | 110  | 0.2919          | 22.7580 |
| 0.1362        | 1.08  | 120  | 0.2897          | 22.0135 |
| 0.0997        | 1.17  | 130  | 0.2915          | 21.3029 |
| 0.0824        | 1.26  | 140  | 0.2920          | 21.4382 |
| 0.0923        | 1.35  | 150  | 0.2918          | 21.3875 |


### Framework versions

- Transformers 4.35.0.dev0
- Pytorch 2.1.0+cu118
- Datasets 2.14.7.dev0
- Tokenizers 0.14.1