---
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: torgo_tiny_finetune_F04_frozen_encoder
  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. -->

# torgo_tiny_finetune_F04_frozen_encoder

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2948
- Wer: 46.1800

## 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: 0.0001
- train_batch_size: 16
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer     |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.7886        | 0.85  | 500   | 0.2527          | 38.2003 |
| 0.0987        | 1.69  | 1000  | 0.2771          | 51.7827 |
| 0.0695        | 2.54  | 1500  | 0.2463          | 38.6248 |
| 0.0479        | 3.39  | 2000  | 0.2699          | 26.8251 |
| 0.0314        | 4.24  | 2500  | 0.2857          | 23.2598 |
| 0.0239        | 5.08  | 3000  | 0.2698          | 23.6842 |
| 0.0173        | 5.93  | 3500  | 0.2771          | 25.2122 |
| 0.0122        | 6.78  | 4000  | 0.2733          | 26.7402 |
| 0.0099        | 7.63  | 4500  | 0.2812          | 26.5705 |
| 0.0091        | 8.47  | 5000  | 0.2773          | 23.4295 |
| 0.0077        | 9.32  | 5500  | 0.2839          | 30.5603 |
| 0.0057        | 10.17 | 6000  | 0.2722          | 23.7691 |
| 0.0043        | 11.02 | 6500  | 0.2959          | 34.3803 |
| 0.0028        | 11.86 | 7000  | 0.2783          | 33.0221 |
| 0.0026        | 12.71 | 7500  | 0.3000          | 32.7674 |
| 0.0025        | 13.56 | 8000  | 0.2865          | 32.6825 |
| 0.0022        | 14.41 | 8500  | 0.2946          | 38.8795 |
| 0.0014        | 15.25 | 9000  | 0.2858          | 38.3701 |
| 0.0012        | 16.1  | 9500  | 0.2953          | 63.8370 |
| 0.0006        | 16.95 | 10000 | 0.2928          | 42.9542 |
| 0.0004        | 17.8  | 10500 | 0.2910          | 43.7182 |
| 0.0004        | 18.64 | 11000 | 0.2947          | 44.8217 |
| 0.0002        | 19.49 | 11500 | 0.2948          | 46.1800 |


### Framework versions

- Transformers 4.32.0
- Pytorch 2.1.0+cu121
- Datasets 2.14.7
- Tokenizers 0.13.3