med_v1_M07 – AI Model by mprzibilla | AlphaNeural AI

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med_v1_M07

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med_v1_M07

This model is a fine-tuned version of facebook/wav2vec2-base on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 3.0346
Wer: 1.0
Cer: 0.9247

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: 0.0002
train_batch_size: 10
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: 2575
num_epochs: 100
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer	Cer
40.0631	5.0	2575	3.4774	1.0	1.0
3.1345	10.0	5150	3.2955	1.0	0.9983
2.8502	15.0	7725	3.1890	1.0	0.9922
2.7005	20.0	10300	3.0885	1.0	0.9784
2.6038	25.0	12875	3.0523	1.0	0.9628
2.5369	30.0	15450	3.0120	1.0	0.9506
2.4897	35.0	18025	3.0113	1.0	0.9463
2.4539	40.0	20600	3.0255	1.0	0.9411
2.4249	45.0	23175	2.9973	1.0	0.9377
2.401	50.0	25750	3.0020	1.0	0.9351
2.3787	55.0	28325	3.0206	1.0	0.9359
2.3686	60.0	30900	3.0332	1.0	0.9333
2.3519	65.0	33475	3.0239	1.0	0.9307
2.3448	70.0	36050	3.0209	1.0	0.9247
2.3341	75.0	38625	3.0215	1.0	0.9273
2.3214	80.0	41200	3.0338	1.0	0.9290
2.3182	85.0	43775	3.0332	1.0	0.9281
2.3169	90.0	46350	3.0343	1.0	0.9238
2.313	95.0	48925	3.0355	1.0	0.9247
2.3115	100.0	51500	3.0346	1.0	0.9247

Framework versions

Transformers 4.18.0
Pytorch 1.10.2+cu102
Datasets 2.3.2
Tokenizers 0.12.1