Hanhpt23/whisper-small-frenchmed-free_E3-11

openai/whisper-small

This model is a fine-tuned version of openai/whisper-small on the pphuc25/FrenchMed dataset. It achieves the following results on the evaluation set:

• Loss: 1.4500
• Wer: 39.8827
• Cer: 27.0125

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: 0.0001
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 100
• num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Wer	Cer
1.0537	1.0	215	1.0242	68.4018	49.4840
0.6061	2.0	430	1.0639	53.3724	32.0077
0.3104	3.0	645	1.1618	54.0323	34.5259
0.1692	4.0	860	1.2151	42.4487	27.3290
0.1085	5.0	1075	1.3178	58.5044	37.6909
0.0834	6.0	1290	1.3759	40.0293	26.5171
0.0523	7.0	1505	1.4465	39.9560	26.5584
0.0448	8.0	1720	1.3777	43.0352	28.1547
0.0342	9.0	1935	1.4440	40.6891	28.8152
0.0292	10.0	2150	1.5108	43.3284	30.2876
0.0156	11.0	2365	1.5093	39.7361	27.3978
0.0173	12.0	2580	1.5143	42.5220	27.9070
0.0088	13.0	2795	1.5168	41.2757	28.4712
0.0045	14.0	3010	1.4740	38.7097	26.3245
0.003	15.0	3225	1.4854	40.0293	27.0951
0.0048	16.0	3440	1.4524	40.3226	26.9850
0.0022	17.0	3655	1.4445	40.6158	27.7694
0.0005	18.0	3870	1.4494	40.3226	27.3841
0.0002	19.0	4085	1.4495	41.0557	27.8932
0.0004	20.0	4300	1.4500	39.8827	27.0125

Framework versions

• Transformers 4.41.1
• Pytorch 2.3.0
• Datasets 2.19.1
• Tokenizers 0.19.1