cohogain/whisper-large-v2-ga-IE

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: 1.0432
• Wer: 32.9559

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
0.2448	1.02	1000	0.8498	41.7538
0.0367	2.04	2000	0.8609	35.7724
0.0095	3.06	3000	0.9109	34.9303
0.0048	4.09	4000	0.9602	34.3496
0.0009	5.11	5000	1.0041	33.2172
0.0003	7.01	6000	1.0362	33.1010
0.0006	8.03	7000	1.0432	32.9559

Framework versions

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