slac-single-head

lengocquangLAB/slac-single-head

slac-single-head is a machine learning model from lengocquangLAB. 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.

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

Downloads · 30 days

14% of all-time downloads

All-time downloads

Public

Parameters

109M

1.8 GB on disk

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.safetensors438 MB · 100%

At a glance

Library: transformers
Model type: bert_model
Access: Public
Created: Apr 2, 2025
Updated: Apr 2, 2025
SHA: c96a4116

Model card

From the Hugging Face model README

slac-single-head

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

Loss: 0.5482
F1 Macro: 0.8380
Precision Macro: 0.8096
Recall Macro: 0.8688
F1 Micro: 0.8552
Precision Micro: 0.8252
Recall Micro: 0.8874

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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 212
num_epochs: 15

Training results

Training Loss	Epoch	Step	Validation Loss	F1 Macro	Precision Macro	Recall Macro	F1 Micro	Precision Micro	Recall Micro
0.6444	1.0	213	0.5045	0.6683	0.5514	0.9416	0.6611	0.5087	0.9437
0.3875	2.0	426	0.3121	0.8016	0.7045	0.9342	0.8214	0.7272	0.9437
0.292	3.0	639	0.3003	0.8095	0.7256	0.9294	0.8265	0.7398	0.9361
0.2172	4.0	852	0.3231	0.8340	0.7807	0.8982	0.8509	0.7973	0.9122
0.1935	5.0	1065	0.3262	0.8262	0.7628	0.9073	0.8445	0.7826	0.9170
0.154	6.0	1278	0.3807	0.8351	0.7975	0.8794	0.8506	0.8183	0.8855
0.1007	7.0	1491	0.4045	0.8297	0.7774	0.8922	0.8456	0.7902	0.9094
0.0866	8.0	1704	0.4100	0.8289	0.7706	0.9010	0.8434	0.7863	0.9094
0.0671	9.0	1917	0.4667	0.8335	0.7981	0.8726	0.8497	0.8127	0.8903
0.0544	10.0	2130	0.5062	0.8412	0.8139	0.8707	0.8557	0.8254	0.8884
0.0482	11.0	2343	0.5141	0.8335	0.8076	0.8616	0.8521	0.8287	0.8769
0.0377	12.0	2556	0.5217	0.8346	0.8022	0.8699	0.8520	0.8194	0.8874
0.0304	13.0	2769	0.5419	0.8370	0.8104	0.8658	0.8537	0.8266	0.8826
0.0307	14.0	2982	0.5397	0.8367	0.8043	0.8721	0.8533	0.8210	0.8884
0.0238	15.0	3195	0.5482	0.8380	0.8096	0.8688	0.8552	0.8252	0.8874

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.3.1
Tokenizers 0.21.0

Library: transformers
Type: bert_model
Created: Apr 2, 2025
Updated: Apr 2, 2025