whisper-large-v2-finetuning-2

This model is a fine-tuned version of guilhermebastos96/whisper-large-v2-finetuning on the common_voice_17_0 dataset. It achieves the following results on the evaluation set:

• Loss: 0.2251
• Wer: 11.8114

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: 6000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0724	0.5089	1000	0.2000	15.6703
0.0322	1.0178	2000	0.2156	12.0592
0.0398	1.5267	3000	0.2065	9.9843
0.0167	2.0356	4000	0.2091	10.5134
0.0107	2.5445	5000	0.2181	13.2453
0.0035	3.0534	6000	0.2251	11.8114

Framework versions

• Transformers 4.42.3
• Pytorch 2.2.1
• Datasets 2.20.0
• Tokenizers 0.19.1