whisper-tiny-Encode-chinesemed – AI Model by Hanhpt23 | AlphaNeural AI

You can deploy this model and start earning money today!

Hanhpt23/
whisper-tiny-Encode-chinesemed

like

0

automatic-speech-recognition

generated_from_trainer

openai/whisper-tiny

endpoints_compatible

Views

No views yet

openai/whisper-tiny

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

Loss: 1.5036
Cer: 34.0018

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	Cer
0.9949	1.0	161	1.1720	86.6756
0.6345	2.0	322	1.2101	74.7772
0.4273	3.0	483	1.2770	42.6025
0.2435	4.0	644	1.3652	44.5856
0.1437	5.0	805	1.4654	50.7353
0.097	6.0	966	1.4137	53.5873
0.0808	7.0	1127	1.4085	42.1569
0.049	8.0	1288	1.4790	38.6586
0.0392	9.0	1449	1.5276	40.6640
0.0283	10.0	1610	1.4854	42.5802
0.0164	11.0	1771	1.5004	39.7727
0.0126	12.0	1932	1.5267	41.9118
0.0124	13.0	2093	1.5349	36.7870
0.0061	14.0	2254	1.5172	35.6061
0.0018	15.0	2415	1.5075	34.0909
0.0032	16.0	2576	1.5066	34.5365
0.001	17.0	2737	1.4948	33.6453
0.0007	18.0	2898	1.5060	34.3137
0.0005	19.0	3059	1.5030	34.2246
0.0005	20.0	3220	1.5036	34.0018

Framework versions

Transformers 4.41.1
Pytorch 2.3.0
Datasets 2.19.1
Tokenizers 0.19.1