CuATR-distilbert-LoRA

chathuru/CuATR-distilbert-LoRA

CuATR-distilbert-LoRA is a machine learning model from chathuru. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.

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

Downloads · 30 days

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Public

Updated Dec 20, 2023

Repo size

23.1 MB

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Hugging Face

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At a glance

License: apache-2.0
Access: Public
Created: Dec 20, 2023
Updated: Dec 20, 2023
SHA: a71ff74a

Base models

Model card

From the Hugging Face model README

CuATR-distilbert-LoRA

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

Loss: 0.6945
Accuracy: 0.5652
F1: 0.7222

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: 2e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 14
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.7007	0.67	1	0.6957	0.5652	0.7222
0.6984	2.0	3	0.6954	0.5652	0.7222
0.7075	2.67	4	0.6952	0.5652	0.7222
0.7	4.0	6	0.6951	0.5652	0.7222
0.6962	4.67	7	0.6950	0.5652	0.7222
0.7003	6.0	9	0.6948	0.5652	0.7222
0.6952	6.67	10	0.6947	0.5652	0.7222
0.7027	8.0	12	0.6946	0.5652	0.7222
0.6995	8.67	13	0.6946	0.5652	0.7222
0.6919	9.33	14	0.6945	0.5652	0.7222

Framework versions

Transformers 4.35.2
Pytorch 2.1.1+cu118
Datasets 2.15.0
Tokenizers 0.15.0

License: apache-2.0
Created: Dec 20, 2023
Updated: Dec 20, 2023