w2v2-base-pretrained_lr5e-5_at0.2_da1 – AI Model by MelanieKoe | AlphaNeural AI

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MelanieKoe/
w2v2-base-pretrained_lr5e-5_at0.2_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_at0.2_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: 1.3038
Wer: 0.1709

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
19.5617	3.91	250	4.1984	1.0
3.3686	7.81	500	3.2319	1.0
3.1228	11.72	750	3.1341	1.0
2.9603	15.62	1000	2.3654	1.0
1.0738	19.53	1250	0.7578	0.5485
0.3549	23.44	1500	0.6579	0.2337
0.2219	27.34	1750	0.8304	0.1999
0.1579	31.25	2000	0.9428	0.1828
0.1216	35.16	2250	1.0046	0.1747
0.0958	39.06	2500	1.0114	0.1751
0.076	42.97	2750	1.2645	0.1768
0.0662	46.88	3000	1.2588	0.1739
0.0569	50.78	3250	1.3057	0.1730
0.0514	54.69	3500	1.2869	0.1696
0.0479	58.59	3750	1.2697	0.1704
0.0451	62.5	4000	1.3038	0.1709

Framework versions

Transformers 4.35.0
Pytorch 2.0.0
Datasets 2.14.6
Tokenizers 0.14.1