w2v2-base-pretrained_lr1e-4_at0.9_da1 – AI Model by MelanieKoe | AlphaNeural AI

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MelanieKoe/
w2v2-base-pretrained_lr1e-4_at0.9_da1

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automatic-speech-recognition

generated_from_trainer

facebook/wav2vec2-base

endpoints_compatible

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w2v2-base-pretrained_lr1e-4_at0.9_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: 6.9410
Wer: 1.0571

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
num_epochs: 60
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
17.8057	6.1	250	4.5611	1.0
3.2734	12.2	500	3.7357	1.0
2.8657	18.29	750	2.7315	1.0
0.3941	24.39	1000	4.7924	1.0529
0.1195	30.49	1250	5.4586	1.0507
0.0721	36.59	1500	6.5058	1.0588
0.0472	42.68	1750	6.8300	1.0614
0.0308	48.78	2000	6.8007	1.0597
0.0247	54.88	2250	6.9410	1.0571

Framework versions

Transformers 4.35.0
Pytorch 2.0.0
Datasets 2.14.6
Tokenizers 0.14.1