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Whisper Large TR - BBS

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

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The following hyperparameters were used during training:

learning_rate: 1e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 32
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
training_steps: 5000
mixed_precision_training: Native AMP

Training Loss	Epoch	Step	Validation Loss	Wer
0.1339	0.8857	1000	0.1939	16.2543
0.0687	1.7715	2000	0.1906	15.3810
0.0341	2.6572	3000	0.1922	15.0570
0.0101	3.5430	4000	0.2055	14.4457
0.0025	4.4287	5000	0.2229	13.8325

Safetensors

Model size

2B params

Tensor type

F32

Base model

Finetuned

(95)

this model