---
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper_finetuned_ver2
  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_finetuned_ver2

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: 0.0048
- Cer: 0.5262
- Wer: 0.4840

## 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: 32
- 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: 500
- training_steps: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Cer    | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|:------:|
| 0.0           | 35.71  | 1000 | 0.0047          | 0.5496 | 0.5227 |
| 0.0001        | 71.43  | 2000 | 0.0048          | 0.5262 | 0.4840 |
| 0.0           | 107.14 | 3000 | 0.0051          | 0.5964 | 0.5615 |
| 0.0           | 142.86 | 4000 | 0.0053          | 0.6080 | 0.5808 |
| 0.0           | 178.57 | 5000 | 0.0054          | 0.6080 | 0.5808 |


### Framework versions

- Transformers 4.40.0.dev0
- Pytorch 2.0.1
- Datasets 2.18.0
- Tokenizers 0.15.2