wav2vec2-xls-r-300m-tonga-test_v2 – AI Model by kalisia | AlphaNeural AI

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wav2vec2-xls-r-300m-tonga-test_v2

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wav2vec2-xls-r-300m-tonga-test_v2

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: 0.4784
Wer: 0.3887
Cer: 0.0940

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: 3e-05
train_batch_size: 2
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 8
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 40
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer	Cer
6.6795	3.62	500	2.9371	1.0	1.0
2.9201	7.25	1000	2.8427	1.0	1.0
2.6938	10.87	1500	1.6109	1.0	0.3506
1.1605	14.49	2000	0.6472	0.5433	0.1229
0.7598	18.12	2500	0.5543	0.4611	0.1092
0.6529	21.74	3000	0.5202	0.4289	0.1026
0.5816	25.36	3500	0.4931	0.4093	0.0981
0.5476	28.98	4000	0.4916	0.4041	0.0978
0.517	32.61	4500	0.4765	0.3948	0.0951
0.5025	36.23	5000	0.4812	0.3879	0.0942
0.4879	39.85	5500	0.4784	0.3887	0.0940

Framework versions

Transformers 4.17.0
Pytorch 1.12.1+cu113
Datasets 1.18.3
Tokenizers 0.13.2