arjunshajitech/whisper-small-malayalam-v2

Whisper Small Malayalam - Arjun Shaji

This model is a fine-tuned version of openai/whisper-small on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:

• Loss: 0.7363
• Wer: 81.6092

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: 1000
• training_steps: 5000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0433	18.5185	500	0.5265	94.7126
0.0144	37.0370	1000	0.5352	89.1954
0.0057	55.5556	1500	0.5989	87.5862
0.0004	74.0741	2000	0.6575	82.0690
0.0	92.5926	2500	0.6616	81.6092
0.0	111.1111	3000	0.6911	81.3793
0.0	129.6296	3500	0.7097	81.3793
0.0	148.1481	4000	0.7232	81.3793
0.0	166.6667	4500	0.7327	81.3793
0.0	185.1852	5000	0.7363	81.6092

Framework versions

• Transformers 4.41.0
• Pytorch 2.3.0+cu121
• Datasets 2.19.1
• Tokenizers 0.19.1