transcribe-arlco-calls

This model is a fine-tuned version of openai/whisper-small.en on the arlco-calls dataset. It achieves the following results on the evaluation set:

• Loss: 0.0040
• Wer: 1.9950

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: 8
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 16
• 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: 20
• training_steps: 400
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.844	2.0	50	0.7820	14.4313
0.3868	4.0	100	0.3769	7.6453
0.1698	6.0	150	0.0941	5.4609
0.0241	8.0	200	0.0248	4.9949
0.0285	10.0	250	0.0102	5.1551
0.007	12.0	300	0.0055	2.2426
0.0027	14.0	350	0.0043	1.9659
0.0031	16.0	400	0.0040	1.9950

Framework versions

• Transformers 4.48.3
• Pytorch 2.5.1+cu124
• Datasets 3.2.0
• Tokenizers 0.21.0