roberta-base-ner-lorafinetune-runs-128-256

pnr-svc/roberta-base-ner-lorafinetune-runs-128-256

roberta-base-ner-lorafinetune-runs-128-256 is a machine learning model from pnr-svc. 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

17% of all-time downloads

All-time downloads

Public

Repo size

100 MB

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.safetensors33.3 MB · 91%

At a glance

Library: peft
License: mit
Access: Public
Created: Oct 4, 2024
Updated: Oct 4, 2024
SHA: c478a58a

Base models

FacebookAI/roberta-base

Model card

From the Hugging Face model README

roberta-base-ner-lorafinetune-runs-128-256

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

Loss: 0.1077
Precision: 0.9467
Recall: 0.9671
F1: 0.9568
Accuracy: 0.9829

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: 0.0004
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.1184	1.0	2643	0.1542	0.9368	0.9538	0.9452	0.9755
0.1116	2.0	5286	0.1153	0.9401	0.9633	0.9515	0.9804
0.0812	3.0	7929	0.1077	0.9467	0.9671	0.9568	0.9829

Framework versions

PEFT 0.12.0
Transformers 4.43.3
Pytorch 2.4.1+cu121
Datasets 2.20.0
Tokenizers 0.19.1

Library: peft
License: mit
Created: Oct 4, 2024
Updated: Oct 4, 2024