whisper-base_trained

This model is a fine-tuned version of openai/whisper-base on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.5384
• Wer: 150.0

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: 4
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 8
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 1
• training_steps: 50

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
2.5874	4.0	6	2.2372	150.0
1.1083	8.0	12	1.4557	150.0
0.6359	12.0	18	1.0874	150.0
0.2396	16.0	24	0.8668	200.0
0.056	20.0	30	0.7220	150.0
0.0147	24.0	36	0.6112	200.0
0.0055	28.0	42	0.5606	200.0
0.0037	32.0	48	0.5384	150.0

Framework versions

• Transformers 4.34.1
• Pytorch 2.1.0+cu118
• Datasets 2.14.5
• Tokenizers 0.14.1