metadata

library_name: transformers
language:
  - en
license: apache-2.0
base_model: openai/whisper-small
tags:
  - generated_from_trainer
datasets:
  - data_tcd_india
metrics:
  - wer
model-index:
  - name: Whisper Small TCD
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: data_tcd
          type: data_tcd_india
          args: 'config: english, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 4.473391433339515

Whisper Small TCD

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

Loss: 0.1792
Wer: 4.4734

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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
training_steps: 3000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0144	3.4364	1000	0.1505	4.5337
0.0012	6.8729	2000	0.1699	4.4641
0.0004	10.3093	3000	0.1792	4.4734

Framework versions

Transformers 4.47.1
Pytorch 2.5.1+cu121
Datasets 3.2.0
Tokenizers 0.21.0