---
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: torgo_tiny_finetune_M02_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_M02_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: 0.2969
- Wer: 44.9915

## 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     |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.7661        | 0.85  | 500   | 0.2672          | 64.6859 |
| 0.0893        | 1.7   | 1000  | 0.2523          | 24.2784 |
| 0.0664        | 2.55  | 1500  | 0.2562          | 20.3735 |
| 0.0439        | 3.4   | 2000  | 0.2674          | 98.8115 |
| 0.0303        | 4.25  | 2500  | 0.2566          | 22.1562 |
| 0.0224        | 5.1   | 3000  | 0.2737          | 24.7878 |
| 0.0164        | 5.95  | 3500  | 0.2761          | 41.3413 |
| 0.0139        | 6.8   | 4000  | 0.2923          | 31.3243 |
| 0.0102        | 7.65  | 4500  | 0.2841          | 45.5008 |
| 0.0082        | 8.5   | 5000  | 0.2913          | 36.5874 |
| 0.0058        | 9.35  | 5500  | 0.3038          | 22.2411 |
| 0.0065        | 10.2  | 6000  | 0.2853          | 22.6655 |
| 0.0052        | 11.05 | 6500  | 0.2806          | 22.4958 |
| 0.0033        | 11.9  | 7000  | 0.2866          | 30.8149 |
| 0.0026        | 12.76 | 7500  | 0.2852          | 24.3633 |
| 0.0027        | 13.61 | 8000  | 0.2956          | 54.4992 |
| 0.0017        | 14.46 | 8500  | 0.2959          | 31.0696 |
| 0.0012        | 15.31 | 9000  | 0.2974          | 35.9932 |
| 0.0012        | 16.16 | 9500  | 0.2993          | 39.5586 |
| 0.0008        | 17.01 | 10000 | 0.2950          | 44.1426 |
| 0.0004        | 17.86 | 10500 | 0.2988          | 47.0289 |
| 0.0002        | 18.71 | 11000 | 0.2948          | 44.2275 |
| 0.0002        | 19.56 | 11500 | 0.2969          | 44.9915 |


### Framework versions

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