tiny_bert_rand_50_v1_mnli

Hartunka/tiny_bert_rand_50_v1_mnli

tiny_bert_rand_50_v1_mnli is a machine learning model from Hartunka. Use it for the machine learning task on the model card, and read the license before you ship it in a product.

should probably proofread and complete it, then remove this comment. --

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At a glance

Model type: distilbert
Access: Public
Created: Apr 16, 2025
Updated: Apr 16, 2025
SHA: 0051c3f1

Base models

Hartunka/tiny_bert_rand_50_v1

Datasets

glue

Model card

From the Hugging Face model README

tiny_bert_rand_50_v1_mnli

This model is a fine-tuned version of Hartunka/tiny_bert_rand_50_v1 on the GLUE MNLI dataset. It achieves the following results on the evaluation set:

Loss: 0.8632
Accuracy: 0.6045

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
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 50

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.9908	1.0	1534	0.9352	0.5470
0.9036	2.0	3068	0.8886	0.5874
0.8527	3.0	4602	0.8672	0.6013
0.8101	4.0	6136	0.8601	0.6128
0.7693	5.0	7670	0.8588	0.6098
0.7296	6.0	9204	0.8737	0.6214
0.6889	7.0	10738	0.8843	0.6221
0.6504	8.0	12272	0.9532	0.6102
0.6127	9.0	13806	0.9572	0.6201
0.5741	10.0	15340	0.9934	0.6180

Framework versions

Transformers 4.40.0
Pytorch 2.6.0+cu124
Datasets 3.5.0
Tokenizers 0.19.1

Type: distilbert
Languages: en
Created: Apr 16, 2025
Updated: Apr 16, 2025