mtl-xlmr-base-dsc-v2

MiuN2k3/mtl-xlmr-base-dsc-v2

mtl-xlmr-base-dsc-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. --

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At a glance

Library: transformers
License: mit
Model type: roberta
Access: Public
Created: Jul 29, 2024
Updated: Jul 30, 2024
SHA: 9b027df1

Base models

Model card

From the Hugging Face model README

mtl-xlmr-base-dsc-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: 0.6635

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
0.8028	1.0	1544	0.8900
0.7137	2.0	3088	0.7217
0.3774	3.0	4632	0.5790
0.3979	4.0	6176	0.5602
0.4717	5.0	7720	0.5559
0.2493	6.0	9264	0.6247
0.2081	7.0	10808	0.5912
0.2637	8.0	12352	0.6284
0.2069	9.0	13896	0.6361
0.1581	10.0	15440	0.6635

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 29, 2024
Updated: Jul 30, 2024