whisper-tiny-Encod-frenchmed – AI Model by Hanhpt23 | AlphaNeural AI

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Hanhpt23/
whisper-tiny-Encod-frenchmed

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automatic-speech-recognition

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openai/whisper-tiny

endpoints_compatible

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openai/whisper-tiny

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

Loss: 1.9773
Wer: 57.9179

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
1.4539	1.0	215	1.4469	192.2287
0.9269	2.0	430	1.4258	127.1994
0.5316	3.0	645	1.5228	66.6422
0.3295	4.0	860	1.6796	60.4839
0.212	5.0	1075	1.7495	73.7537
0.1228	6.0	1290	1.8167	78.9589
0.0766	7.0	1505	1.8370	80.0587
0.0617	8.0	1720	1.8817	61.1437
0.0575	9.0	1935	1.9629	88.0499
0.0319	10.0	2150	1.9228	58.3578
0.0266	11.0	2365	1.9362	57.1848
0.0143	12.0	2580	1.9740	57.1848
0.0124	13.0	2795	1.9917	86.9501
0.0109	14.0	3010	1.9632	56.5982
0.0087	15.0	3225	1.9501	60.8504
0.0048	16.0	3440	1.9785	55.7918
0.0034	17.0	3655	1.9765	58.6510
0.0021	18.0	3870	1.9765	56.8915
0.0007	19.0	4085	1.9737	58.3578
0.0007	20.0	4300	1.9773	57.9179

Framework versions

Transformers 4.41.1
Pytorch 2.3.0
Datasets 2.19.1
Tokenizers 0.19.1