metadata

language:
  - en
license: apache-2.0
base_model: openai/whisper-small
tags:
  - generated_from_trainer
datasets:
  - mShiry/ATC_combined
metrics:
  - wer
model-index:
  - name: Whisper Small ATC - ATCText
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: ATC
          type: mShiry/ATC_combined
          args: 'split: test'
        metrics:
          - name: Wer
            type: wer
            value: 10.612930650580948

Whisper Small ATC - ATCText

This model is a fine-tuned version of openai/whisper-small on the ATC dataset. It achieves the following results on the evaluation set:

Loss: 0.2486
Wer: 10.6129

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: 8
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

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.2533	0.42	1000	0.3465	16.2868
0.235	0.84	2000	0.2881	13.5237
0.0851	1.27	3000	0.2607	10.6048
0.1317	1.69	4000	0.2486	10.6129

Framework versions

Transformers 4.39.3
Pytorch 2.2.2
Datasets 2.18.0
Tokenizers 0.15.2