khier12/120min_whisper_small_FT_5e-5

120min_whisper_small_FT_

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: 0.9793
• Wer: 73.6089
• Cer: 35.0299

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: 5e-05
• train_batch_size: 2
• eval_batch_size: 4
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 4
• optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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: 400
• training_steps: 1500
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer	Cer
1.3278	0.3817	100	1.0068	70.3920	26.3073
1.011	0.7634	200	0.9279	69.9889	28.5998
0.783	1.1450	300	0.9639	70.0364	28.7620
0.6481	1.5267	400	1.0095	76.7942	36.6462
0.7387	1.9084	500	0.9869	72.6842	30.8710
0.3726	2.2901	600	1.0133	71.2298	28.8136
0.3741	2.6718	700	0.9793	73.6089	35.0299

Framework versions

• Transformers 4.57.3
• Pytorch 2.9.0+cu126
• Datasets 2.21.0
• Tokenizers 0.22.2