whisper-base-speech-commands

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

• Loss: 1.1307
• Accuracy: 0.8067

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: 96
• eval_batch_size: 96
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 20
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.2604	1.0	412	1.0617	0.7977
0.1168	2.0	824	1.0024	0.8017
0.1527	3.0	1236	0.9757	0.8022
0.0637	4.0	1648	1.0066	0.8004
0.0631	5.0	2060	1.0504	0.8053
0.0554	6.0	2472	1.1307	0.8067
0.1075	7.0	2884	1.1664	0.8017
0.021	8.0	3296	1.4746	0.8044
0.0144	9.0	3708	1.3729	0.8044
0.0158	10.0	4120	1.3561	0.8040
0.0504	11.0	4532	1.3289	0.8053

Framework versions

• Transformers 4.43.3
• Pytorch 2.2.2+cu121
• Datasets 2.18.0
• Tokenizers 0.19.1