w2v2-base-pretrained_lr5e-5_at0.8_da0.6 – AI Model by MelanieKoe | AlphaNeural AI

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MelanieKoe/
w2v2-base-pretrained_lr5e-5_at0.8_da0.6

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automatic-speech-recognition

generated_from_trainer

facebook/wav2vec2-base

endpoints_compatible

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w2v2-base-pretrained_lr5e-5_at0.8_da0.6

This model is a fine-tuned version of facebook/wav2vec2-base on the None dataset. It achieves the following results on the evaluation set:

Loss: 2.3139
Wer: 0.1773

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: 5e-05
train_batch_size: 32
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: 1000
training_steps: 4000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
22.3022	8.93	250	14.1336	1.0
7.1613	17.86	500	12.5928	1.0
4.3974	26.79	750	12.3385	1.0
4.139	35.71	1000	9.3127	1.0
3.3971	44.64	1250	3.0328	1.0
1.9421	53.57	1500	1.4361	0.7381
0.2784	62.5	1750	1.4964	0.2896
0.1222	71.43	2000	1.7459	0.2559
0.0769	80.36	2250	2.0649	0.2255
0.0559	89.29	2500	2.2779	0.1892
0.0432	98.21	2750	2.2997	0.1901
0.036	107.14	3000	2.2112	0.1871
0.0309	116.07	3250	2.3675	0.1867
0.028	125.0	3500	2.3204	0.1820
0.0252	133.93	3750	2.3129	0.1803
0.0238	142.86	4000	2.3139	0.1773

Framework versions

Transformers 4.35.0
Pytorch 2.0.0
Datasets 2.14.6
Tokenizers 0.14.1