You can deploy this model and start earning money today!

Hanhpt23/
whisper-medium-Encod-frenchmed

Name: whisper-medium-Encod-frenchmed
Rating: 2.5 (6 reviews)

transformers

safetensors

whisper

automatic-speech-recognition

generated_from_trainer

openai/whisper-medium

finetune

apache-2.0

endpoints_compatible

Views

No views yet

openai/whisper-medium

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

Loss: 1.8094
Wer: 45.6012

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
1.2928	1.0	215	1.2902	56.6716
0.8083	2.0	430	1.4740	75.1466
0.4531	3.0	645	1.4275	64.5161
0.316	4.0	860	1.6528	53.3724
0.1942	5.0	1075	1.7240	61.3636
0.1557	6.0	1290	1.6985	46.1877
0.1254	7.0	1505	1.8613	52.6393
0.1052	8.0	1720	1.7694	50.6598
0.0719	9.0	1935	1.7321	45.8944
0.0606	10.0	2150	1.8430	49.7801
0.0446	11.0	2365	1.8449	49.7801
0.0387	12.0	2580	1.8400	51.6862
0.0305	13.0	2795	1.8258	57.1114
0.0138	14.0	3010	1.9455	50.1466
0.0104	15.0	3225	1.7864	50.8065
0.0117	16.0	3440	1.8213	46.3343
0.0034	17.0	3655	1.7827	44.5748
0.0023	18.0	3870	1.7990	44.2082
0.0007	19.0	4085	1.8095	44.4282
0.0008	20.0	4300	1.8094	45.6012

Framework versions

Transformers 4.41.1
Pytorch 2.3.0
Datasets 2.19.1
Tokenizers 0.19.1

Hanhpt23/whisper-medium-Encod-frenchmed

openai/whisper-medium

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Hanhpt23/
whisper-medium-Encod-frenchmed