finetune_v2

This model is a fine-tuned version of openai/whisper-large-v3 on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.2649
• Wer: 0.5208

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-06
• train_batch_size: 32
• eval_batch_size: 16
• seed: 42
• distributed_type: multi-GPU
• 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: 1
• training_steps: 13
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
No log	3.0	3	0.3357	0.0
No log	6.0	6	0.3242	0.0
No log	9.0	9	0.3003	0.0
No log	12.0	12	0.2649	0.5208

Framework versions

• Transformers 4.41.2
• Pytorch 2.2.0
• Datasets 2.20.0
• Tokenizers 0.19.1