rishabhjain16/whisper_medium_to_myst_cmu

openai/whisper-medium

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

• Loss: 0.3246
• Wer: 341.9230

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: 32
• eval_batch_size: 32
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 500
• training_steps: 4000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.2032	0.12	500	0.2243	493.2750
0.1192	1.1	1000	0.2127	424.6297
0.1109	2.08	1500	0.2237	351.5590
0.042	3.06	2000	0.2460	165.9201
0.0262	4.04	2500	0.2909	231.2864
0.0139	5.02	3000	0.3042	350.0223
0.0084	6.0	3500	0.3247	327.0151
0.0023	6.13	4000	0.3246	341.9230

Framework versions

• Transformers 4.27.0.dev0
• Pytorch 1.13.1+cu117
• Datasets 2.9.1.dev0
• Tokenizers 0.13.2