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---
language:
- en
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- jlvdoorn/atco2-asr-atcosim
metrics:
- wer
model-index:
- name: Whisper Small En - Whisper with atco2-asr-atcosim
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: 'This is a dataset constructed from two datasets: ATCO2-ASR and ATCOSIM.'
type: jlvdoorn/atco2-asr-atcosim
args: 'config: en, split: test'
metrics:
- name: Wer
type: wer
value: 0.02577651759247326
---
<!-- 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 Small En - Whisper with atco2-asr-atcosim
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the This is a dataset constructed from two datasets: ATCO2-ASR and ATCOSIM. dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0010
- Wer: 0.0258
## 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: 4000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 0.0637 | 1.9763 | 1000 | 0.0962 | 7.4365 |
| 0.0154 | 3.9526 | 2000 | 0.0163 | 2.3972 |
| 0.002 | 5.9289 | 3000 | 0.0027 | 1.5015 |
| 0.0003 | 7.9051 | 4000 | 0.0010 | 0.0258 |
### Framework versions
- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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