w2v2-base-pretrained_lr5e-5_at1_da1 – AI Model by MelanieKoe | AlphaNeural AI

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MelanieKoe/
w2v2-base-pretrained_lr5e-5_at1_da1

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automatic-speech-recognition

generated_from_trainer

facebook/wav2vec2-base

endpoints_compatible

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w2v2-base-pretrained_lr5e-5_at1_da1

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: 2.3753
Wer: 0.1837

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
18.9508	6.1	250	4.5541	1.0
3.4223	12.2	500	3.2365	1.0
3.1022	18.29	750	3.1107	1.0
2.0891	24.39	1000	1.2943	0.4930
0.2477	30.49	1250	1.4675	0.2208
0.1323	36.59	1500	1.8152	0.2067
0.0908	42.68	1750	1.8821	0.1931
0.0721	48.78	2000	2.1984	0.2008
0.0584	54.88	2250	2.0544	0.1927
0.0483	60.98	2500	2.0092	0.1845
0.0437	67.07	2750	2.1545	0.1837
0.0347	73.17	3000	2.3775	0.1918
0.0331	79.27	3250	2.4051	0.1880
0.0302	85.37	3500	2.3556	0.1790
0.0279	91.46	3750	2.3822	0.1858
0.026	97.56	4000	2.3753	0.1837

Framework versions

Transformers 4.35.0
Pytorch 2.0.0
Datasets 2.14.6
Tokenizers 0.14.1