wav2vec2-base-ks-linear_lrX1000 – AI Model by Jungwoo4021 | AlphaNeural AI

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Jungwoo4021/
wav2vec2-base-ks-linear_lrX1000

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text-classification

audio-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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wav2vec2-base-ks-linear_lrX1000

This model is a fine-tuned version of facebook/wav2vec2-base on the superb dataset. It achieves the following results on the evaluation set:

Loss: 0.5661
Accuracy: 0.8325

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: 0.03
train_batch_size: 256
eval_batch_size: 256
seed: 0
gradient_accumulation_steps: 4
total_train_batch_size: 1024
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 10.0
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.7558	1.0	50	1.0584	0.6462
0.5971	2.0	100	0.7816	0.7510
0.5382	3.0	150	0.7870	0.7520
0.5045	4.0	200	0.6647	0.7880
0.4717	5.0	250	1.1572	0.6053
0.4651	6.0	300	0.6387	0.7945
0.4205	7.0	350	0.5661	0.8325
0.4423	8.0	400	0.7100	0.7846
0.426	9.0	450	0.7054	0.7829
0.4067	10.0	500	0.6288	0.8114

Framework versions

Transformers 4.22.0.dev0
Pytorch 1.11.0+cu115
Datasets 2.4.0
Tokenizers 0.12.1