cohogain/whisper-medium-ga-IE-cv11-fleurs-livaud

openai/whisper-medium

This model is a fine-tuned version of openai/whisper-medium on the common_voice_11_0 dataset. It achieves the following results on the evaluation set:

• Loss: 1.1422
• Wer: 35.2207

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: 8
• 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: 7000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.1137	4.02	1000	0.9072	40.0987
0.0153	9.02	2000	1.0351	38.7631
0.0042	14.01	3000	1.0507	36.4402
0.0013	19.0	4000	1.0924	36.2660
0.0003	23.02	5000	1.1422	35.2207
0.0001	28.02	6000	1.1688	35.3368
0.0001	33.01	7000	1.1768	35.5110

Framework versions

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