---
license: apache-2.0
base_model: openai/whisper-tiny.en
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-tiny.en-atcosim
  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. -->

# whisper-tiny.en-atcosim

This model is a fine-tuned version of [openai/whisper-tiny.en](https://huggingface.co/openai/whisper-tiny.en) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0737
- Wer: 2.7135

## 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: 1e-05
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 10
- num_epochs: 100

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.4068        | 8.33  | 500  | 0.0639          | 2.4958 |
| 0.0021        | 16.67 | 1000 | 0.0638          | 2.3245 |
| 0.0006        | 25.0  | 1500 | 0.0665          | 2.3338 |
| 0.0003        | 33.33 | 2000 | 0.0680          | 2.2736 |
| 0.0002        | 41.67 | 2500 | 0.0693          | 2.3893 |
| 0.0001        | 50.0  | 3000 | 0.0703          | 2.4634 |
| 0.0001        | 58.33 | 3500 | 0.0713          | 2.4449 |
| 0.0001        | 66.67 | 4000 | 0.0720          | 2.4542 |
| 0.0001        | 75.0  | 4500 | 0.0727          | 2.4588 |
| 0.0001        | 83.33 | 5000 | 0.0732          | 2.6394 |
| 0.0001        | 91.67 | 5500 | 0.0736          | 2.7783 |
| 0.0001        | 100.0 | 6000 | 0.0737          | 2.7135 |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.2
- Datasets 2.15.0
- Tokenizers 0.15.0