---
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: torgo_tiny_finetune_M01_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_M01_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: 0.2864
- Wer: 45.6706

## 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     |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.768         | 0.85  | 500   | 0.2601          | 25.8913 |
| 0.0914        | 1.7   | 1000  | 0.2569          | 99.8302 |
| 0.0699        | 2.55  | 1500  | 0.2626          | 39.3039 |
| 0.042         | 3.4   | 2000  | 0.2691          | 26.0611 |
| 0.0336        | 4.24  | 2500  | 0.2619          | 25.4669 |
| 0.0229        | 5.09  | 3000  | 0.2613          | 29.2020 |
| 0.0166        | 5.94  | 3500  | 0.2525          | 30.0509 |
| 0.0112        | 6.79  | 4000  | 0.2843          | 30.7301 |
| 0.0113        | 7.64  | 4500  | 0.2862          | 25.8913 |
| 0.0085        | 8.49  | 5000  | 0.2726          | 29.5416 |
| 0.0059        | 9.34  | 5500  | 0.2782          | 35.6537 |
| 0.0052        | 10.19 | 6000  | 0.2971          | 39.6435 |
| 0.0041        | 11.04 | 6500  | 0.2886          | 26.9949 |
| 0.0043        | 11.88 | 7000  | 0.2952          | 29.2869 |
| 0.0031        | 12.73 | 7500  | 0.2858          | 34.3803 |
| 0.0022        | 13.58 | 8000  | 0.2844          | 35.9083 |
| 0.0019        | 14.43 | 8500  | 0.2749          | 33.7861 |
| 0.0013        | 15.28 | 9000  | 0.2882          | 41.3413 |
| 0.0014        | 16.13 | 9500  | 0.2817          | 44.3973 |
| 0.0008        | 16.98 | 10000 | 0.2872          | 39.7284 |
| 0.0006        | 17.83 | 10500 | 0.2846          | 41.8506 |
| 0.0003        | 18.68 | 11000 | 0.2900          | 45.2462 |
| 0.0003        | 19.52 | 11500 | 0.2864          | 45.6706 |


### Framework versions

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