license, base_model, tags, datasets, metrics, model-index

license	base_model	tags	datasets	metrics	model-index
apache-2.0	openai/whisper-small	generated_from_trainer	mozilla-foundation/common_voice_17_0	wer	name results whisper-small-id task dataset metrics name type Automatic Speech Recognition automatic-speech-recognition name type config split args mozilla-foundation/common_voice_17_0 id mozilla-foundation/common_voice_17_0 id None id name type value Wer wer 0.05902826117221217

whisper-small-id

This model is a fine-tuned version of openai/whisper-small on the mozilla-foundation/common_voice_17_0 id dataset. It achieves the following results on the evaluation set:

• Loss: 0.0878
• Wer: 0.0590 (5.9%)

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
• gradient_accumulation_steps: 2
• total_train_batch_size: 32
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 500
• training_steps: 20000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.1875	0.8457	1000	0.1400	0.1099
0.0852	1.6913	2000	0.1043	0.0857
0.0387	2.5370	3000	0.0914	0.0757
0.0153	3.3827	4000	0.0860	0.0818
0.008	4.2283	5000	0.0878	0.0698
0.005	5.0740	6000	0.0878	0.0745
0.0033	5.9197	7000	0.0834	0.0651
0.0029	6.7653	8000	0.0815	0.0627
0.0014	7.6110	9000	0.0853	0.0627
0.0013	8.4567	10000	0.0861	0.0641
0.0005	9.3023	11000	0.0857	0.0633
0.0005	10.1480	12000	0.0856	0.0620
0.0007	10.9937	13000	0.0866	0.0605
0.0005	11.8393	14000	0.0871	0.0614
0.0002	12.6850	15000	0.0850	0.0596
0.0004	13.5307	16000	0.0849	0.0600
0.0001	14.3763	17000	0.0868	0.0592
0.0002	15.2220	18000	0.0873	0.0593
0.0001	16.0677	19000	0.0875	0.0585
0.0001	16.9133	20000	0.0878	0.0590

Framework versions

• Transformers 4.42.0.dev0
• Pytorch 2.3.0+cu121
• Datasets 2.19.1
• Tokenizers 0.19.1