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

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MelanieKoe/
w2v2-base-pretrained_lr1e-4_at0.4_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_at0.4_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: 6.1307
Wer: 1.0580

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
14.7571	8.06	500	3.6451	1.0
1.7406	16.13	1000	3.2148	1.0448
0.2001	24.19	1500	4.3045	1.0345
0.0734	32.26	2000	5.3205	1.0516
0.0402	40.32	2500	5.5110	1.0477
0.0254	48.39	3000	5.8453	1.0554
0.0161	56.45	3500	6.1307	1.0580

Framework versions

Transformers 4.35.0
Pytorch 2.0.0
Datasets 2.14.6
Tokenizers 0.14.1