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

# output_dir

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: 1.9986
- Wer: 98.7061

## 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: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- 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      |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 1.9269        | 1.0152 | 1000 | 1.9970          | 98.8909  |
| 1.1741        | 2.0305 | 2000 | 1.9986          | 98.7061  |
| 0.5248        | 3.0457 | 3000 | 2.0790          | 102.4030 |
| 0.2094        | 4.0609 | 4000 | 2.1701          | 104.2514 |
| 0.086         | 5.0761 | 5000 | 2.2254          | 106.2847 |


### Framework versions

- Transformers 4.44.1
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1