---
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: torgo_tiny_finetune_M03_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_M03_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: 0.3051
- Wer: 41.5959

## 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     |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.7806        | 0.85  | 500   | 0.2631          | 52.1222 |
| 0.0945        | 1.71  | 1000  | 0.2804          | 34.4652 |
| 0.071         | 2.56  | 1500  | 0.2464          | 22.5806 |
| 0.0455        | 3.41  | 2000  | 0.2476          | 21.3073 |
| 0.0335        | 4.27  | 2500  | 0.2581          | 21.2224 |
| 0.0253        | 5.12  | 3000  | 0.2617          | 25.0424 |
| 0.0177        | 5.97  | 3500  | 0.2898          | 26.4007 |
| 0.0127        | 6.83  | 4000  | 0.3068          | 24.5331 |
| 0.0111        | 7.68  | 4500  | 0.2925          | 41.9355 |
| 0.0087        | 8.53  | 5000  | 0.3179          | 23.2598 |
| 0.0064        | 9.39  | 5500  | 0.2884          | 29.8812 |
| 0.0056        | 10.24 | 6000  | 0.2952          | 35.4839 |
| 0.0037        | 11.09 | 6500  | 0.2956          | 26.4007 |
| 0.0035        | 11.95 | 7000  | 0.2839          | 27.3345 |
| 0.0028        | 12.8  | 7500  | 0.2975          | 28.3531 |
| 0.0019        | 13.65 | 8000  | 0.3129          | 42.3599 |
| 0.0018        | 14.51 | 8500  | 0.2932          | 31.5789 |
| 0.0015        | 15.36 | 9000  | 0.3047          | 32.0883 |
| 0.0008        | 16.21 | 9500  | 0.3071          | 37.4363 |
| 0.0008        | 17.06 | 10000 | 0.3081          | 39.8981 |
| 0.0006        | 17.92 | 10500 | 0.3064          | 39.5586 |
| 0.0003        | 18.77 | 11000 | 0.3052          | 40.2377 |
| 0.0002        | 19.62 | 11500 | 0.3051          | 41.5959 |


### Framework versions

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