whisper-tiny-frenchmed-v1 – AI Model by Hanhpt23 | AlphaNeural AI

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Hanhpt23/
whisper-tiny-frenchmed-v1

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automatic-speech-recognition

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openai/whisper-tiny

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openai/whisper-tiny

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

Loss: 1.9080
Wer: 56.1584

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
1.3284	1.0	215	1.3160	94.5748
0.8758	2.0	430	1.3129	84.3842
0.5092	3.0	645	1.3872	57.4047
0.295	4.0	860	1.4638	70.3079
0.1646	5.0	1075	1.5513	69.0616
0.0939	6.0	1290	1.6665	60.6305
0.0585	7.0	1505	1.7200	54.8387
0.0411	8.0	1720	1.6980	54.1789
0.0295	9.0	1935	1.7985	56.0850
0.023	10.0	2150	1.8064	57.1114
0.0106	11.0	2365	1.8492	54.3255
0.011	12.0	2580	1.8559	57.2581
0.0087	13.0	2795	1.8624	59.5308
0.0069	14.0	3010	1.8581	57.1114
0.0028	15.0	3225	1.8776	58.1378
0.002	16.0	3440	1.8993	56.5982
0.0023	17.0	3655	1.8775	56.5249
0.0011	18.0	3870	1.9031	56.8915
0.0009	19.0	4085	1.9053	55.9384
0.0009	20.0	4300	1.9080	56.1584

Framework versions

Transformers 4.41.1
Pytorch 2.3.0
Datasets 2.19.1
Tokenizers 0.19.1