model_wav2vec_ – AI Model by linl03 | AlphaNeural AI

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linl03/
model_wav2vec_

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automatic-speech-recognition

generated_from_trainer

facebook/wav2vec2-base

endpoints_compatible

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model_wav2vec_

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: 0.4608
Wer: 0.3361

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: 16
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: 30
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
3.5101	2.01	500	1.6030	1.0221
0.7158	4.02	1000	0.4599	0.4587
0.2914	6.02	1500	0.4092	0.4037
0.1906	8.03	2000	0.3927	0.3865
0.1328	10.04	2500	0.4067	0.3810
0.1122	12.05	3000	0.4128	0.3645
0.0954	14.06	3500	0.4469	0.3621
0.0754	16.06	4000	0.4296	0.3639
0.0589	18.07	4500	0.4434	0.3567
0.0497	20.08	5000	0.4597	0.3535
0.0455	22.09	5500	0.4854	0.3454
0.0395	24.1	6000	0.4615	0.3435
0.0328	26.1	6500	0.4714	0.3396
0.0284	28.11	7000	0.4608	0.3361

Framework versions

Transformers 4.36.2
Pytorch 2.1.0+cu121
Datasets 1.18.3
Tokenizers 0.15.0