w2v2-base-pretrained_lr5e-5_at0.8_da0.05 – AI Model by MelanieKoe | AlphaNeural AI

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MelanieKoe/
w2v2-base-pretrained_lr5e-5_at0.8_da0.05

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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_da0.05

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: 3.9827
Wer: 1.0295

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
43.0808	83.33	250	28.8440	1.0
8.5391	166.67	500	3.7744	1.0
3.2564	250.0	750	3.1400	1.0
3.0586	333.33	1000	3.1144	1.0
2.9982	416.67	1250	3.0792	1.0
2.927	500.0	1500	3.0777	1.0
2.7925	583.33	1750	3.0732	1.0
2.577	666.67	2000	3.0084	1.0
2.2523	750.0	2250	2.9828	1.0
1.8719	833.33	2500	3.1056	1.0026
1.5177	916.67	2750	3.3320	1.0154
1.233	1000.0	3000	3.5057	1.0184
1.0527	1083.33	3250	3.7065	1.0325
0.9262	1166.67	3500	3.8646	1.0316
0.8456	1250.0	3750	3.9958	1.0295
0.8247	1333.33	4000	3.9827	1.0295

Framework versions

Transformers 4.35.0
Pytorch 2.0.0
Datasets 2.14.6
Tokenizers 0.14.1