whisper-small-hi-en-ru-lang-id

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

• Loss: 4.4504
• Accuracy: 0.5096
• F1: 0.4801

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: 0.0001
• train_batch_size: 2
• eval_batch_size: 2
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 8
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.1
• training_steps: 1000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.0001	1.5936	500	4.3275	0.4994	0.4399
0.0	3.1873	1000	4.4504	0.5096	0.4801

Framework versions

• Transformers 4.44.2
• Pytorch 2.2.1+cu121
• Datasets 3.0.0
• Tokenizers 0.19.1