whisper-tiny-finetuned-minds14

This model is a fine-tuned version of openai/whisper-tiny on the PolyAI/minds14 dataset. It achieves the following results on the evaluation set:

• Loss: 0.6785
• Wer Ortho: 0.3607
• Wer: 0.3624

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: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: constant_with_warmup
• lr_scheduler_warmup_ratio: 0.1
• lr_scheduler_warmup_steps: 50
• training_steps: 500
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer Ortho	Wer
3.8342	1.0	28	2.7013	0.4859	0.3669
1.52	2.0	56	0.6447	0.3822	0.3624
0.4282	3.0	84	0.5154	0.3573	0.3521
0.2511	4.0	112	0.5017	0.3452	0.3430
0.1461	5.0	140	0.5106	0.3620	0.3572
0.0829	6.0	168	0.5399	0.3641	0.3592
0.0423	7.0	196	0.5596	0.3573	0.3527
0.0199	8.0	224	0.5846	0.3627	0.3598
0.0093	9.0	252	0.6006	0.3594	0.3572
0.0056	10.0	280	0.6207	0.3345	0.3301
0.0037	11.0	308	0.6238	0.3560	0.3534
0.0021	12.0	336	0.6377	0.3486	0.3482
0.0016	13.0	364	0.6485	0.3594	0.3579
0.0013	14.0	392	0.6621	0.3567	0.3572
0.0011	15.0	420	0.6617	0.3587	0.3605
0.0009	16.0	448	0.6682	0.3560	0.3559
0.0008	17.0	476	0.6741	0.3627	0.3624
0.0008	17.86	500	0.6785	0.3607	0.3624

Framework versions

• Transformers 4.37.2
• Pytorch 2.1.2
• Datasets 2.1.0
• Tokenizers 0.15.1