---
language:
- en
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- Jzuluaga/atcosim_corpus
metrics:
- wer
model-index:
- name: Whisper Base ATCOSIM
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: atcosim_corpus_numbers_converted
      type: Jzuluaga/atcosim_corpus
      args: 'config: en, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 404.9337012855893
---

<!-- 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 Base ATCOSIM

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the atcosim_corpus_numbers_converted dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5964
- Wer: 404.9337

## 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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer      |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 8.7316        | 0.2092 | 100  | 8.1521          | 110.7020 |
| 5.3768        | 0.4184 | 200  | 5.2758          | 110.9713 |
| 3.2842        | 0.6276 | 300  | 3.4243          | 119.1492 |
| 1.892         | 0.8368 | 400  | 2.1743          | 121.4377 |
| 0.9999        | 1.0460 | 500  | 1.4513          | 168.8160 |
| 0.6472        | 1.2552 | 600  | 1.0157          | 369.7449 |
| 0.529         | 1.4644 | 700  | 0.8372          | 356.8554 |
| 0.4086        | 1.6736 | 800  | 0.6973          | 300.4644 |
| 0.3559        | 1.8828 | 900  | 0.6164          | 361.0150 |
| 0.2302        | 2.0921 | 1000 | 0.5964          | 404.9337 |


### Framework versions

- Transformers 4.42.0.dev0
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1