distilbert_sa_GLUE_Experiment_logit_kd_mnli_256 – AI Model by gokuls | AlphaNeural AI

You can deploy this model and start earning money today!

gokuls/
distilbert_sa_GLUE_Experiment_logit_kd_mnli_256

like

0

text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

Views

No views yet

distilbert_sa_GLUE_Experiment_logit_kd_mnli_256

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: 0.5305
Accuracy: 0.5881

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
0.5834	1.0	1534	0.5611	0.5153
0.5545	2.0	3068	0.5469	0.5330
0.5418	3.0	4602	0.5420	0.5477
0.5323	4.0	6136	0.5382	0.5633
0.5235	5.0	7670	0.5333	0.5743
0.5153	6.0	9204	0.5315	0.5753
0.5078	7.0	10738	0.5295	0.5832
0.5005	8.0	12272	0.5313	0.5821
0.4939	9.0	13806	0.5281	0.5949
0.4873	10.0	15340	0.5298	0.5895
0.481	11.0	16874	0.5263	0.6010
0.4748	12.0	18408	0.5288	0.6041
0.469	13.0	19942	0.5288	0.6031
0.463	14.0	21476	0.5336	0.6056
0.4574	15.0	23010	0.5296	0.6072
0.4523	16.0	24544	0.5358	0.6096

Framework versions

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