---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- luigisaetta/atco2_normalized_augmented
metrics:
- wer
model-index:
- name: whisper-atco2-medium
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: luigisaetta/atco2_normalized_augmented
      type: luigisaetta/atco2_normalized_augmented
      config: en
      split: test
    metrics:
    - name: Wer
      type: wer
      value: 17.50524109014675
---

<!-- 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-atco2-medium

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the luigisaetta/atco2_normalized_augmented dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6129
- Wer: 17.5052

## 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: 2
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- training_steps: 500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 2.3939        | 1.06  | 50   | 1.8493          | 66.5618 |
| 0.5127        | 2.13  | 100  | 0.5119          | 30.6080 |
| 0.0626        | 3.19  | 150  | 0.5410          | 20.4403 |
| 0.0157        | 4.25  | 200  | 0.5775          | 19.8113 |
| 0.0107        | 5.32  | 250  | 0.5552          | 19.7065 |
| 0.0044        | 6.38  | 300  | 0.5723          | 18.1342 |
| 0.0013        | 7.45  | 350  | 0.5763          | 17.7149 |
| 0.0005        | 8.51  | 400  | 0.6053          | 17.7149 |
| 0.0004        | 9.57  | 450  | 0.6109          | 17.5052 |
| 0.0004        | 10.64 | 500  | 0.6129          | 17.5052 |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.11.0