ts_tg

kmcs-casulit/ts_tg

ts_tg is a machine learning model from kmcs-casulit. 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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Hugging Face

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At a glance

License: mit
Model type: deberta-v2
Access: Public
Created: Aug 5, 2024
Updated: Aug 5, 2024
SHA: 64a7e73c

Base models

microsoft/deberta-v3-small

Model card

From the Hugging Face model README

ts_tg

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

Loss: 0.0516
Accuracy: 0.8517
F1: 0.8759
Precision: 0.8996
Recall: 0.8533

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: 128
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 8

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
No log	1.0	202	0.1370	0.5242	0.6378	0.8129	0.5248
No log	2.0	404	0.0857	0.6877	0.7700	0.8749	0.6875
0.1567	3.0	606	0.0667	0.7810	0.8331	0.8929	0.7809
0.1567	4.0	808	0.0593	0.8145	0.8525	0.8947	0.8142
0.0566	5.0	1010	0.0554	0.8406	0.8668	0.8926	0.8425
0.0566	6.0	1212	0.0529	0.8437	0.8718	0.8994	0.8459
0.0566	7.0	1414	0.0522	0.8474	0.8737	0.8992	0.8496
0.0383	8.0	1616	0.0516	0.8517	0.8759	0.8996	0.8533

Framework versions

Transformers 4.42.4
Pytorch 2.3.1+cu121
Datasets 2.20.0
Tokenizers 0.19.1

Type: deberta-v2
License: mit
Created: Aug 5, 2024
Updated: Aug 5, 2024