---
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: torgo_tiny_finetune_M04_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_M04_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: 0.2842
- Wer: 39.5586

## 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     |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.7695        | 0.84  | 500   | 0.2502          | 52.2920 |
| 0.0895        | 1.69  | 1000  | 0.2592          | 39.9830 |
| 0.069         | 2.53  | 1500  | 0.2494          | 22.3260 |
| 0.0465        | 3.37  | 2000  | 0.2667          | 29.6265 |
| 0.0311        | 4.22  | 2500  | 0.2489          | 20.4584 |
| 0.0241        | 5.06  | 3000  | 0.2731          | 23.1749 |
| 0.0156        | 5.9   | 3500  | 0.2608          | 30.3056 |
| 0.0127        | 6.75  | 4000  | 0.2944          | 25.2971 |
| 0.0102        | 7.59  | 4500  | 0.2818          | 25.8913 |
| 0.008         | 8.43  | 5000  | 0.2610          | 25.1273 |
| 0.0079        | 9.27  | 5500  | 0.2632          | 24.6180 |
| 0.0054        | 10.12 | 6000  | 0.2776          | 29.4567 |
| 0.0047        | 10.96 | 6500  | 0.2758          | 28.0985 |
| 0.003         | 11.8  | 7000  | 0.2744          | 26.9949 |
| 0.0033        | 12.65 | 7500  | 0.2875          | 22.0713 |
| 0.0022        | 13.49 | 8000  | 0.2842          | 34.7199 |
| 0.0019        | 14.33 | 8500  | 0.2776          | 29.7963 |
| 0.0012        | 15.18 | 9000  | 0.2850          | 35.2292 |
| 0.0012        | 16.02 | 9500  | 0.2770          | 28.9474 |
| 0.0006        | 16.86 | 10000 | 0.2797          | 56.3667 |
| 0.0006        | 17.71 | 10500 | 0.2807          | 37.0119 |
| 0.0002        | 18.55 | 11000 | 0.2849          | 36.7572 |
| 0.0002        | 19.39 | 11500 | 0.2842          | 39.5586 |


### Framework versions

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