whisper-large-v2-paper_

This model is a fine-tuned version of openai/whisper-large-v2 on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.4133
• Wer: 47.7467

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	0.3626	71.8596
No log	2.0	286	0.3398	50.4925
No log	3.0	429	0.3426	52.2600
0.3684	4.0	572	0.3541	46.2800
0.3684	5.0	715	0.3721	46.6114
0.3684	6.0	858	0.4133	47.7467

Framework versions

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