phayathaibert-intent-classification-sports-facility

unduood/phayathaibert-intent-classification-sports-facility

phayathaibert-intent-classification-sports-facility is a text classification model from unduood. Use it when you need a label for a piece of text. It is set up for transformers.

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

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At a glance

Task: Text Classification
Library: transformers
Model type: camembert
Access: Public
Created: Jan 7, 2026
Updated: Jan 7, 2026
SHA: 0dcd31f6

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Base models

clicknext/phayathaibert

Model card

From the Hugging Face model README

phayathaibert-intent-classification-sports-facility

This model is a fine-tuned version of clicknext/phayathaibert on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.0738
F1 Micro: 0.9611
Precision Micro: 0.9640
Recall Micro: 0.9582
F1 Macro: 0.9660
Precision Macro: 0.9656
Recall Macro: 0.9668
F1 Samples: 0.9636
Hamming Loss: 0.0262
Exact Match: 0.9095
F1 Feedback: 0.9398
F1 Complaint: 0.9763
F1 Question: 0.9679
F1 Off-topic: 0.98

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: 16
eval_batch_size: 32
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 32
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 10
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	F1 Micro	Precision Micro	Recall Micro	F1 Macro	Precision Macro	Recall Macro	F1 Samples	Hamming Loss	Exact Match	F1 Feedback	F1 Complaint	F1 Question	F1 Off-topic
0.4141	0.7968	100	0.2455	0.8833	0.8969	0.8701	0.8890	0.9014	0.8770	0.8822	0.0772	0.7555	0.8566	0.9167	0.8882	0.8945
0.1248	1.5896	200	0.1132	0.9393	0.9552	0.9239	0.9455	0.9535	0.9391	0.9442	0.0401	0.8697	0.9050	0.9488	0.9674	0.9608
0.0746	2.3825	300	0.0987	0.9470	0.9615	0.9328	0.9507	0.9613	0.9410	0.9492	0.0351	0.8778	0.9317	0.9481	0.9576	0.9655
0.0651	3.1753	400	0.0824	0.9560	0.9553	0.9567	0.9609	0.9587	0.9631	0.9603	0.0296	0.8918	0.9310	0.9521	0.9853	0.9751
0.0446	3.9721	500	0.0837	0.9595	0.9653	0.9537	0.9653	0.9692	0.9616	0.9630	0.0271	0.9038	0.9341	0.9658	0.9765	0.9849
0.0337	4.7649	600	0.0845	0.9559	0.9580	0.9537	0.9619	0.9643	0.9597	0.9612	0.0296	0.8998	0.9333	0.9592	0.9701	0.9849
0.0244	5.5578	700	0.0854	0.9583	0.9568	0.9597	0.9635	0.9619	0.9653	0.9635	0.0281	0.9058	0.9389	0.9622	0.9681	0.9849
0.0186	6.3506	800	0.0933	0.9533	0.9620	0.9448	0.9577	0.9639	0.9518	0.9576	0.0311	0.8978	0.9363	0.9553	0.9641	0.9751

Framework versions

Transformers 4.57.3
Pytorch 2.9.0+cu126
Datasets 4.0.0
Tokenizers 0.22.1

Task: Text Classification
Library: transformers
Type: camembert
Created: Jan 7, 2026
Updated: Jan 7, 2026