deberta-v3-base-finetuned-autext23_s2

andricValdez/deberta-v3-base-finetuned-autext23_s2

deberta-v3-base-finetuned-autext23_s2 is a machine learning model from andricValdez. 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 mit.

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

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At a glance

License: mit
Model type: deberta-v2
Access: Public
Created: Dec 6, 2024
Updated: Dec 6, 2024
SHA: c88e5515

Base models

microsoft/deberta-v3-base

Model card

From the Hugging Face model README

deberta-v3-base-finetuned-autext23_s2

This model is a fine-tuned version of microsoft/deberta-v3-base on the None dataset. It achieves the following results on the evaluation set:

Loss: 1.0620
Accuracy: 0.5731
F1: 0.5648

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: 64
eval_batch_size: 64
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
No log	1.0	246	0.9935	0.5587	0.5371
1.1328	2.0	492	0.9254	0.5792	0.5592
1.1328	3.0	738	0.9501	0.5801	0.5692
0.7267	4.0	984	1.0345	0.5619	0.5509
0.7267	5.0	1230	1.0620	0.5731	0.5648

Framework versions

Transformers 4.40.1
Pytorch 2.3.0+cu121
Datasets 2.19.0
Tokenizers 0.19.1

Type: deberta-v2
License: mit
Created: Dec 6, 2024
Updated: Dec 6, 2024