Hanhpt23/whisper-small-frenchmed-free_E0-8D0-8

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: 1.3133
• Wer: 40.9824
• Cer: 29.0078

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
0.9467	1.0	215	0.9214	52.4194	46.7318
0.4998	2.0	430	0.9703	53.0792	36.7002
0.2067	3.0	645	1.0581	40.7625	26.8749
0.1092	4.0	860	1.1350	63.1965	43.3329
0.0699	5.0	1075	1.1698	40.6158	26.9988
0.0602	6.0	1290	1.1891	51.3930	32.2279
0.0409	7.0	1505	1.2566	53.5191	34.8424
0.036	8.0	1720	1.2424	39.8827	27.3841
0.0183	9.0	1935	1.2718	39.8094	26.1869
0.0125	10.0	2150	1.2755	37.6833	25.6915
0.0072	11.0	2365	1.3042	39.4428	27.0125
0.0118	12.0	2580	1.2765	44.3548	30.6591
0.0062	13.0	2795	1.2951	40.7625	28.5537
0.0045	14.0	3010	1.2897	40.4692	28.2923
0.0005	15.0	3225	1.3089	42.0088	29.4344
0.0018	16.0	3440	1.3013	42.2287	29.3794
0.0004	17.0	3655	1.3101	41.1290	29.4069
0.0003	18.0	3870	1.3113	40.9824	29.0216
0.0002	19.0	4085	1.3128	40.9824	29.0078
0.0002	20.0	4300	1.3133	40.9824	29.0078

Framework versions

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