whisper-base-atcosim

This model is a fine-tuned version of openai/whisper-base on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.0620
• Wer: 2.9820

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: 128
• eval_batch_size: 128
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 10
• num_epochs: 100

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.152	8.33	500	0.0522	2.5282
0.001	16.67	1000	0.0539	3.0608
0.0003	25.0	1500	0.0556	3.0237
0.0002	33.33	2000	0.0567	3.0237
0.0001	41.67	2500	0.0579	3.0144
0.0001	50.0	3000	0.0588	2.9959
0.0001	58.33	3500	0.0597	3.0052
0.0001	66.67	4000	0.0604	3.0098
0.0	75.0	4500	0.0610	2.9867
0.0	83.33	5000	0.0615	2.9867
0.0	91.67	5500	0.0619	2.9774
0.0	100.0	6000	0.0620	2.9820

Framework versions

• Transformers 4.36.2
• Pytorch 2.1.2
• Datasets 2.15.0
• Tokenizers 0.15.0