metadata

license: apache-2.0
base_model: openai/whisper-large-v3
tags:
  - generated_from_trainer
datasets:
  - DewiBrynJones/oscar-cy-tts
metrics:
  - wer
model-index:
  - name: whisper-large-v3-ft-tts-cy
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: DewiBrynJones/oscar-cy-tts default
          type: DewiBrynJones/oscar-cy-tts
          args: default
        metrics:
          - name: Wer
            type: wer
            value: 0.1561639017527405

whisper-large-v3-ft-tts-cy

This model is a fine-tuned version of openai/whisper-large-v3 on the DewiBrynJones/oscar-cy-tts default dataset. It achieves the following results on the evaluation set:

Loss: 0.2108
Wer: 0.1562

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: 16
seed: 42
gradient_accumulation_steps: 2
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: 500
training_steps: 5000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.3429	0.2627	1000	0.3296	0.2300
0.2636	0.5255	2000	0.2615	0.1926
0.2316	0.7882	3000	0.2340	0.1798
0.1779	1.0510	4000	0.2179	0.1624
0.1626	1.3137	5000	0.2108	0.1562

Framework versions

Transformers 4.44.0
Pytorch 2.4.0+cu121
Datasets 2.20.0
Tokenizers 0.19.1