parambharat/whisper-tiny-ta-example

Whisper tiny Ta example - Bharat Ramanathan

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

• Loss: 0.4016
• Wer: 36.5217

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: 16
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 64
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 25
• training_steps: 100
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.304	12.01	25	0.3614	31.7391
0.1826	24.02	50	0.3851	35.2174
0.1346	37.01	75	0.3999	37.8261
0.1096	49.02	100	0.4016	36.5217

Framework versions

• Transformers 4.26.0.dev0
• Pytorch 1.13.0
• Datasets 2.7.1.dev0
• Tokenizers 0.13.2