w2v2-base-pretrained_lr1e-4_at0.8_da0.3 – AI Model by MelanieKoe | AlphaNeural AI

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MelanieKoe/
w2v2-base-pretrained_lr1e-4_at0.8_da0.3

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automatic-speech-recognition

generated_from_trainer

facebook/wav2vec2-base

endpoints_compatible

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w2v2-base-pretrained_lr1e-4_at0.8_da0.3

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: 2.2956
Wer: 0.1811

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: 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: 3500
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
21.7228	17.86	250	3.7139	1.0
3.1757	35.71	500	3.1149	1.0
2.8079	53.57	750	1.7093	1.0038
0.301	71.43	1000	1.4764	0.2443
0.0637	89.29	1250	1.7091	0.2200
0.0311	107.14	1500	1.7022	0.2055
0.021	125.0	1750	2.0876	0.2016
0.0154	142.86	2000	2.2718	0.1974
0.0114	160.71	2250	2.1541	0.1845
0.0089	178.57	2500	2.2868	0.1854
0.0074	196.43	2750	2.3831	0.1914
0.0062	214.29	3000	2.2381	0.1841
0.0054	232.14	3250	2.4147	0.1824
0.0056	250.0	3500	2.2956	0.1811

Framework versions

Transformers 4.35.0
Pytorch 2.0.0
Datasets 2.14.6
Tokenizers 0.14.1