transformers tensorboard safetensors whisper automatic-speech-recognition generated_from_trainer base_model:openai/whisper-small license:apache-2.0 endpoints_compatible region:us
---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- wer
base_model: openai/whisper-small
model-index:
- name: whisper-fine_tuning
  results: []
---

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# whisper-fine_tuning

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: 4.4096
- Wer: 89.7704

## 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-06
- train_batch_size: 8
- 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: 10
- training_steps: 100
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 5.127         | 0.04  | 10   | 6.5305          | 89.7704 |
| 4.9407        | 0.08  | 20   | 5.6702          | 88.1002 |
| 3.9127        | 0.12  | 30   | 5.2648          | 85.1775 |
| 3.4678        | 0.16  | 40   | 5.0057          | 84.7599 |
| 3.7416        | 0.2   | 50   | 4.8397          | 85.3862 |
| 3.1575        | 0.24  | 60   | 4.6961          | 86.4301 |
| 3.3175        | 0.28  | 70   | 4.5819          | 87.2651 |
| 2.9554        | 0.32  | 80   | 4.4950          | 88.1002 |
| 3.0291        | 0.36  | 90   | 4.4375          | 89.7704 |
| 3.0219        | 0.4   | 100  | 4.4096          | 89.7704 |


### Framework versions

- Transformers 4.38.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
