whisper-small-mn-11

This model is a fine-tuned version of openai/whisper-small on the None dataset. It achieves the following results on the evaluation set:

• Loss: 1.0138
• Wer: 51.9664
• Cer: 19.8770

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: 32
• eval_batch_size: 32
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 500
• training_steps: 15000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer	Cer
0.0025	32.26	1000	0.8913	53.6214	20.6866
0.0007	64.52	2000	0.9326	52.1685	19.5991
0.0001	96.77	3000	1.0138	51.9664	19.8770
0.0001	129.03	4000	1.0639	52.1248	19.9178
0.0	161.29	5000	1.1236	52.0428	19.9652
0.0	193.55	6000	1.1677	52.4634	20.0351
0.0	225.81	7000	1.2224	52.5836	20.1258
0.0	258.06	8000	1.2633	52.7310	20.2073
0.0	290.32	9000	1.3152	52.8184	20.2273
0.0	322.58	10000	1.3530	52.9495	20.3080
0.0	354.84	11000	1.3995	53.0260	20.3088
0.0	387.1	12000	1.4306	52.9878	20.2057
0.0	419.35	13000	1.4674	52.9714	20.3113
0.0	451.61	14000	1.4859	52.9386	20.2947
0.0	483.87	15000	1.4994	52.9768	20.3280

Framework versions

• Transformers 4.26.0.dev0
• Pytorch 1.13.0+cu117
• Datasets 2.7.1.dev0
• Tokenizers 0.13.2