distilbert_add_GLUE_Experiment_logit_kd_rte_96 – AI Model by gokuls | AlphaNeural AI

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gokuls/
distilbert_add_GLUE_Experiment_logit_kd_rte_96

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text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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distilbert_add_GLUE_Experiment_logit_kd_rte_96

This model is a fine-tuned version of distilbert-base-uncased on the GLUE RTE dataset. It achieves the following results on the evaluation set:

Loss: 0.4234
Accuracy: 0.4729

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: 5e-05
train_batch_size: 256
eval_batch_size: 256
seed: 10
distributed_type: multi-GPU
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 50
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.4604	1.0	10	0.4429	0.4729
0.4358	2.0	20	0.4328	0.4729
0.4282	3.0	30	0.4290	0.4729
0.4246	4.0	40	0.4269	0.4729
0.4227	5.0	50	0.4252	0.4729
0.4204	6.0	60	0.4243	0.4729
0.4191	7.0	70	0.4238	0.4729
0.4185	8.0	80	0.4235	0.4729
0.4175	9.0	90	0.4234	0.4729
0.4164	10.0	100	0.4235	0.4729
0.418	11.0	110	0.4236	0.4729
0.4169	12.0	120	0.4236	0.4729
0.4173	13.0	130	0.4238	0.4729
0.4168	14.0	140	0.4239	0.4729

Framework versions

Transformers 4.26.0
Pytorch 1.14.0a0+410ce96
Datasets 2.9.0
Tokenizers 0.13.2