distilhubert-ft-common-language – AI Model by anton-l | AlphaNeural AI

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anton-l/
distilhubert-ft-common-language

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audio-classification

generated_from_trainer

common_language

endpoints_compatible

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distilhubert-ft-common-language

This model is a fine-tuned version of ntu-spml/distilhubert on the common_language dataset. It achieves the following results on the evaluation set:

Loss: 2.7214
Accuracy: 0.2797

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: 32
eval_batch_size: 4
seed: 0
gradient_accumulation_steps: 4
total_train_batch_size: 128
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
3.6543	1.0	173	3.7611	0.0491
3.2221	2.0	346	3.4868	0.1352
2.9332	3.0	519	3.2732	0.1861
2.7299	4.0	692	3.0944	0.2172
2.5638	5.0	865	2.9790	0.2400
2.3871	6.0	1038	2.8668	0.2590
2.3384	7.0	1211	2.7972	0.2653
2.2648	8.0	1384	2.7625	0.2695
2.2162	9.0	1557	2.7405	0.2782
2.1915	10.0	1730	2.7214	0.2797

Framework versions

Transformers 4.12.0.dev0
Pytorch 1.9.1+cu111
Datasets 1.14.0
Tokenizers 0.10.3