distilbert_sa_GLUE_Experiment_mnli_96 – AI Model by gokuls | AlphaNeural AI

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gokuls/
distilbert_sa_GLUE_Experiment_mnli_96

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text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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distilbert_sa_GLUE_Experiment_mnli_96

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

Loss: 0.9288
Accuracy: 0.5545

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
1.0498	1.0	1534	0.9988	0.5084
0.9757	2.0	3068	0.9532	0.5303
0.9458	3.0	4602	0.9435	0.5377
0.9272	4.0	6136	0.9306	0.5456
0.9122	5.0	7670	0.9305	0.5474
0.8992	6.0	9204	0.9294	0.5489
0.8867	7.0	10738	0.9260	0.5522
0.8752	8.0	12272	0.9319	0.5559
0.8645	9.0	13806	0.9336	0.5604
0.8545	10.0	15340	0.9200	0.5629
0.8443	11.0	16874	0.9200	0.5664
0.8338	12.0	18408	0.9298	0.5672
0.8252	13.0	19942	0.9383	0.5647
0.8168	14.0	21476	0.9428	0.5691
0.8084	15.0	23010	0.9325	0.5730

Framework versions

Transformers 4.26.0
Pytorch 1.14.0a0+410ce96
Datasets 2.8.0
Tokenizers 0.13.2