Hanhpt23/whisper-small-frenchmed-free_ED0-8

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: 1.3219
• Wer: 50.2199
• Cer: 33.0948

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
0.9164	1.0	215	0.8750	53.6657	38.7230
0.5	2.0	430	0.9152	52.4927	36.3837
0.1918	3.0	645	1.0102	54.8387	36.1222
0.0742	4.0	860	1.1064	54.4721	44.0209
0.0514	5.0	1075	1.1371	44.5748	32.1178
0.0395	6.0	1290	1.1607	57.3314	46.4703
0.0233	7.0	1505	1.1898	41.9355	28.8978
0.0181	8.0	1720	1.2267	39.2229	26.8474
0.017	9.0	1935	1.2296	39.1496	28.0033
0.0083	10.0	2150	1.2535	55.3519	36.4800
0.0013	11.0	2365	1.2872	51.6129	34.8287
0.0028	12.0	2580	1.2961	37.9765	27.2465
0.0005	13.0	2795	1.3004	50.2199	33.4251
0.0008	14.0	3010	1.3092	50.1466	33.2187
0.0004	15.0	3225	1.3065	51.6129	34.2645
0.0008	16.0	3440	1.3133	49.7801	32.5857
0.0005	17.0	3655	1.3164	50.2199	33.1499
0.0002	18.0	3870	1.3198	50.0	32.9847
0.0002	19.0	4085	1.3213	50.2933	33.0673
0.0002	20.0	4300	1.3219	50.2199	33.0948

Framework versions

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