---
base_model: openai/whisper-small
datasets:
- arrow
license: apache-2.0
metrics:
- wer
tags:
- generated_from_trainer
model-index:
- name: c_dialect
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: arrow
      type: arrow
      config: default
      split: validation
      args: default
    metrics:
    - type: wer
      value: 4.318792583946361
      name: Wer
---

<!-- 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. -->

# c_dialect

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the arrow dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0342
- Wer: 4.3188

## 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: 5
- eval_batch_size: 5
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 99
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 0.0301        | 1.4583 | 3500 | 0.0460          | 5.8606 |
| 0.0089        | 2.9167 | 7000 | 0.0342          | 4.3188 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1