distilbert_sa_GLUE_Experiment_logit_kd_rte_192 – AI Model by gokuls | AlphaNeural AI

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gokuls/
distilbert_sa_GLUE_Experiment_logit_kd_rte_192

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text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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distilbert_sa_GLUE_Experiment_logit_kd_rte_192

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: 0.4228
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
0.4351	1.0	10	0.4238	0.4729
0.4173	2.0	20	0.4246	0.4729
0.4173	3.0	30	0.4238	0.4729
0.4169	4.0	40	0.4237	0.4729
0.4185	5.0	50	0.4242	0.4729
0.4171	6.0	60	0.4237	0.4729
0.417	7.0	70	0.4237	0.4729
0.4175	8.0	80	0.4240	0.4729
0.4166	9.0	90	0.4235	0.4729
0.416	10.0	100	0.4236	0.4729
0.4174	11.0	110	0.4244	0.4729
0.4153	12.0	120	0.4234	0.4729
0.416	13.0	130	0.4238	0.4729
0.4134	14.0	140	0.4228	0.4729
0.4042	15.0	150	0.4279	0.4729
0.3771	16.0	160	0.4453	0.4621
0.3491	17.0	170	0.4650	0.4513
0.3258	18.0	180	0.4842	0.4729
0.3064	19.0	190	0.4996	0.4621

Framework versions

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