---
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: torgo_tiny_finetune_F03_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_F03_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: 0.0487
- Wer: 34.9794

## 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   | 0.0571          | 14.9520 |
| 0.0987        | 1.69  | 1000  | 0.0536          | 50.3429 |
| 0.0695        | 2.54  | 1500  | 0.0480          | 4.3896  |
| 0.0479        | 3.39  | 2000  | 0.0534          | 7.9561  |
| 0.0314        | 4.24  | 2500  | 0.0542          | 5.0754  |
| 0.0239        | 5.08  | 3000  | 0.0438          | 5.0754  |
| 0.0173        | 5.93  | 3500  | 0.0399          | 7.8189  |
| 0.0122        | 6.78  | 4000  | 0.0402          | 7.4074  |
| 0.0099        | 7.63  | 4500  | 0.0384          | 5.0754  |
| 0.0091        | 8.47  | 5000  | 0.0380          | 4.6639  |
| 0.0077        | 9.32  | 5500  | 0.0400          | 9.6022  |
| 0.0057        | 10.17 | 6000  | 0.0361          | 8.0933  |
| 0.0043        | 11.02 | 6500  | 0.0377          | 15.9122 |
| 0.0028        | 11.86 | 7000  | 0.0338          | 15.6379 |
| 0.0026        | 12.71 | 7500  | 0.0407          | 16.7353 |
| 0.0025        | 13.56 | 8000  | 0.0404          | 16.3237 |
| 0.0022        | 14.41 | 8500  | 0.0387          | 13.3059 |
| 0.0014        | 15.25 | 9000  | 0.0373          | 19.4787 |
| 0.0012        | 16.1  | 9500  | 0.0414          | 25.2401 |
| 0.0006        | 16.95 | 10000 | 0.0475          | 28.3951 |
| 0.0004        | 17.8  | 10500 | 0.0435          | 30.3155 |
| 0.0004        | 18.64 | 11000 | 0.0480          | 32.0988 |
| 0.0002        | 19.49 | 11500 | 0.0487          | 34.9794 |


### Framework versions

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