---
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper Fine-tuned - NNCES
  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 Fine-tuned - NNCES

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1135
- Wer: 8.0963

## 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: 4
- 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: 100
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 1.2697        | 0.1   | 10   | 0.8252          | 40.9920 |
| 0.6597        | 0.2   | 20   | 0.5482          | 25.2371 |
| 0.4656        | 0.3   | 30   | 0.3488          | 20.0584 |
| 0.2774        | 0.4   | 40   | 0.2164          | 21.5901 |
| 0.1746        | 0.5   | 50   | 0.1770          | 19.0372 |
| 0.1826        | 0.6   | 60   | 0.1540          | 15.3902 |
| 0.1228        | 0.7   | 70   | 0.1364          | 11.4515 |
| 0.1271        | 0.8   | 80   | 0.1246          | 8.6798  |
| 0.2388        | 0.9   | 90   | 0.1165          | 8.0233  |
| 0.2584        | 1.0   | 100  | 0.1135          | 8.0963  |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1