ashpandian/audio_speech_recognition-1b-ATC

Whisper-large-v3-atc

This model is a fine-tuned version of openai/whisper-large-v3 on the atc_dataset dataset. It achieves the following results on the evaluation set:

• Loss: 0.2187
• Wer: 7.4754

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: 500
• training_steps: 4000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.19	0.8446	1000	0.2450	9.4369
0.1105	1.6892	2000	0.2092	8.4916
0.047	2.5338	3000	0.2069	7.9794
0.017	3.3784	4000	0.2187	7.4754

Framework versions

• Transformers 4.41.2
• Pytorch 2.3.0+cu121
• Datasets 2.19.2
• Tokenizers 0.19.1