wav2vec2-large-xls-r-300m-gl-jupyter9 – AI Model by 4m1g0 | AlphaNeural AI

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wav2vec2-large-xls-r-300m-gl-jupyter9

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wav2vec2-large-xls-r-300m-gl-jupyter9

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.0970
Wer: 0.0624

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: 0.0003
train_batch_size: 16
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 60
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
3.6977	3.36	400	0.4273	0.4574
0.2282	6.72	800	0.1492	0.1723
0.0884	10.08	1200	0.1344	0.1336
0.0594	13.44	1600	0.1329	0.1238
0.0437	16.8	2000	0.1137	0.1153
0.0384	20.17	2400	0.1197	0.1033
0.0332	23.53	2800	0.1147	0.0980
0.0282	26.89	3200	0.1079	0.0917
0.0236	30.25	3600	0.1144	0.0922
0.0237	33.61	4000	0.1130	0.0880
0.019	36.97	4400	0.1035	0.0818
0.0164	40.33	4800	0.1045	0.0813
0.0146	43.69	5200	0.1037	0.0735
0.0111	47.06	5600	0.1085	0.0701
0.0093	50.42	6000	0.1039	0.0659
0.0084	53.78	6400	0.0970	0.0636
0.0073	57.14	6800	0.0970	0.0624

Framework versions

Transformers 4.11.3
Pytorch 1.9.1+cu111
Datasets 1.18.3
Tokenizers 0.10.3