---
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: torgo_tiny_finetune_M05_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_M05_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: 0.2755
- Wer: 40.5772

## 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     |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.7762        | 0.84  | 500   | 0.2681          | 42.3599 |
| 0.0927        | 1.68  | 1000  | 0.2688          | 26.0611 |
| 0.0703        | 2.53  | 1500  | 0.2827          | 27.6740 |
| 0.0457        | 3.37  | 2000  | 0.2467          | 22.4109 |
| 0.0318        | 4.21  | 2500  | 0.2900          | 21.8166 |
| 0.0225        | 5.05  | 3000  | 0.2947          | 23.9389 |
| 0.0173        | 5.89  | 3500  | 0.2752          | 22.3260 |
| 0.0127        | 6.73  | 4000  | 0.2749          | 22.7504 |
| 0.0112        | 7.58  | 4500  | 0.2957          | 22.4109 |
| 0.008         | 8.42  | 5000  | 0.2765          | 23.3447 |
| 0.0071        | 9.26  | 5500  | 0.2780          | 30.3056 |
| 0.0049        | 10.1  | 6000  | 0.2827          | 23.5144 |
| 0.0045        | 10.94 | 6500  | 0.2884          | 34.5501 |
| 0.0036        | 11.78 | 7000  | 0.2605          | 36.1630 |
| 0.0028        | 12.63 | 7500  | 0.2787          | 30.5603 |
| 0.0024        | 13.47 | 8000  | 0.2758          | 31.5789 |
| 0.0016        | 14.31 | 8500  | 0.2801          | 33.1919 |
| 0.0018        | 15.15 | 9000  | 0.2779          | 33.9559 |
| 0.0011        | 15.99 | 9500  | 0.2737          | 37.2666 |
| 0.0008        | 16.84 | 10000 | 0.2757          | 31.5789 |
| 0.0005        | 17.68 | 10500 | 0.2787          | 35.6537 |
| 0.0004        | 18.52 | 11000 | 0.2747          | 35.9083 |
| 0.0003        | 19.36 | 11500 | 0.2755          | 40.5772 |


### Framework versions

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