whisper-large-paper_

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

• Loss: 0.4374
• Wer: 47.9863

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: 2e-05
• train_batch_size: 24
• eval_batch_size: 24
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 500
• num_epochs: 6

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
No log	1.0	143	0.3754	47.3394
No log	2.0	286	0.3418	44.5511
No log	3.0	429	0.3522	47.7507
0.3895	4.0	572	0.3795	48.9312
0.3895	5.0	715	0.4091	51.5160
0.3895	6.0	858	0.4374	47.9863

Framework versions

• Transformers 4.31.0.dev0
• Pytorch 2.0.0+cu117
• Datasets 2.7.0
• Tokenizers 0.13.2