mtl-xlmr-base-viwiki-v2

MiuN2k3/mtl-xlmr-base-viwiki-v2

mtl-xlmr-base-viwiki-v2 is a machine learning model from MiuN2k3. 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 transformers. The card lists the license as mit.

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

Downloads · 30 days

6% of all-time downloads

All-time downloads

Public

Parameters

277M

11.1 GB on disk

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.safetensors1.1 GB · 100%

At a glance

Library: transformers
License: mit
Model type: roberta
Access: Public
Created: Jul 31, 2024
Updated: Jul 31, 2024
SHA: be6f3d99

Base models

Model card

From the Hugging Face model README

mtl-xlmr-base-viwiki-v2

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: 0.6919

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: 1e-05
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
lr_scheduler_warmup_ratio: 0.05
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss
0.7756	1.0	960	0.7972
0.6104	2.0	1920	0.6775
0.5942	3.0	2880	0.6227
0.6037	4.0	3840	0.6349
0.5208	5.0	4800	0.5975
0.347	6.0	5760	0.6008
0.415	7.0	6720	0.6142
0.3473	8.0	7680	0.6252
0.3312	9.0	8640	0.6748
0.2134	10.0	9600	0.6919

Framework versions

Transformers 4.43.3
Pytorch 2.2.1
Datasets 2.20.0
Tokenizers 0.19.1

Library: transformers
Type: roberta
License: mit
Created: Jul 31, 2024
Updated: Jul 31, 2024