Hanhpt23/whisper-small-frenchmed-free_E0-8D3-11

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: 1.2572
• Wer: 36.5103
• Cer: 24.3842

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
0.91	1.0	215	0.9039	45.0880	31.1133
0.5486	2.0	430	0.8982	84.3109	51.1766
0.284	3.0	645	0.9864	52.4194	33.9480
0.1557	4.0	860	1.0088	52.8592	33.5902
0.0909	5.0	1075	1.0402	41.7155	28.7601
0.0734	6.0	1290	1.0860	58.2845	37.2781
0.0444	7.0	1505	1.0962	51.2463	37.2643
0.0238	8.0	1720	1.1381	48.3871	32.9434
0.0213	9.0	1935	1.1168	35.4106	24.4117
0.0205	10.0	2150	1.1998	38.3431	25.5264
0.0097	11.0	2365	1.1861	36.1437	24.7970
0.0041	12.0	2580	1.2100	53.8123	35.1589
0.0033	13.0	2795	1.2308	37.6100	25.8291
0.004	14.0	3010	1.2381	37.0235	24.8245
0.0014	15.0	3225	1.2263	35.5572	23.1595
0.0009	16.0	3440	1.2465	35.0440	23.3246
0.0006	17.0	3655	1.2452	36.3636	24.8383
0.0007	18.0	3870	1.2525	35.5572	23.6411
0.0004	19.0	4085	1.2560	36.4370	24.3292
0.0004	20.0	4300	1.2572	36.5103	24.3842

Framework versions

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