distilbert_qlora

Siyinggu/distilbert_qlora

distilbert_qlora is a machine learning model from Siyinggu. 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. --

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Public

Updated Aug 11, 2024

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19.2 MB

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Hugging Face

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At a glance

License: apache-2.0
Access: Public
Created: Aug 11, 2024
Updated: Aug 11, 2024
SHA: 31621cf1

Base models

Model card

From the Hugging Face model README

distilbert_qlora

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: 0.6173
Accuracy: 0.8934

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: 0.0002
train_batch_size: 1
eval_batch_size: 1
seed: 42
gradient_accumulation_steps: 16
total_train_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: constant
lr_scheduler_warmup_ratio: 0.03
training_steps: 1875

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.7159	0.0958	187	0.7154	0.8574
0.6637	0.1916	374	0.6786	0.8730
0.6898	0.2874	561	0.6563	0.8795
0.7074	0.3832	748	0.6493	0.8833
0.6035	0.4790	935	0.6531	0.8857
0.6173	0.5748	1122	0.6369	0.8866
0.6508	0.6706	1309	0.6367	0.8889
0.6849	0.7664	1496	0.6180	0.8921
0.6642	0.8622	1683	0.6231	0.8932
0.6412	0.9580	1870	0.6173	0.8934

Framework versions

Transformers 4.43.4
Pytorch 2.3.1+cu121
Datasets 2.20.0
Tokenizers 0.19.1

License: apache-2.0
Created: Aug 11, 2024
Updated: Aug 11, 2024