loha_fine_tuned_boolq_XLMroberta

tjasad/loha_fine_tuned_boolq_XLMroberta

loha_fine_tuned_boolq_XLMroberta is a machine learning model from tjasad. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft. The card lists the license as mit.

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

Downloads · 30 days

41% of all-time downloads

All-time downloads

Public

Repo size

29.3 MB

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.json17.1 MB · 58%

At a glance

Library: peft
License: mit
Access: Public
Created: May 23, 2024
Updated: May 23, 2024
SHA: 6fc65c22

Base models

Model card

From the Hugging Face model README

loha_fine_tuned_boolq_XLMroberta

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

Loss: 0.5831
Accuracy: 0.7778
F1: 0.6806

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: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
training_steps: 400

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.6993	4.1667	50	0.6280	0.7778	0.6806
0.6581	8.3333	100	0.5915	0.7778	0.6806
0.6619	12.5	150	0.5941	0.7778	0.6806
0.6547	16.6667	200	0.5880	0.7778	0.6806
0.6558	20.8333	250	0.5883	0.7778	0.6806
0.6554	25.0	300	0.5868	0.7778	0.6806
0.6598	29.1667	350	0.5841	0.7778	0.6806
0.6581	33.3333	400	0.5831	0.7778	0.6806

Framework versions

PEFT 0.11.1
Transformers 4.40.2
Pytorch 2.3.0+cu121
Datasets 2.19.1
Tokenizers 0.19.1

Library: peft
License: mit
Created: May 23, 2024
Updated: May 23, 2024