te-zsc-synthetic_5ep_2805

adriansanz/te-zsc-synthetic_5ep_2805

te-zsc-synthetic_5ep_2805 is a text classification model from adriansanz. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as apache-2.0.

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

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At a glance

Task: Text Classification
Library: transformers
License: apache-2.0
Model type: roberta
Access: Public
Created: May 28, 2024
Updated: May 28, 2024
SHA: 0f1bdc34

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Base models

projecte-aina/roberta-base-ca-v2-cased-te

Model card

From the Hugging Face model README

080524_epoch_5

This model is a fine-tuned version of projecte-aina/roberta-base-ca-v2-cased-te on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.3399
Accuracy: 0.981
Precision: 0.9810
Recall: 0.981
F1: 0.9810
Ratio: 0.495

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: 10
eval_batch_size: 2
seed: 47
gradient_accumulation_steps: 2
total_train_batch_size: 20
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.06
lr_scheduler_warmup_steps: 4
num_epochs: 1
label_smoothing_factor: 0.1

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1	Ratio
0.3013	0.0333	10	0.3474	0.978	0.9783	0.978	0.9780	0.488
0.3087	0.0667	20	0.3471	0.979	0.9790	0.979	0.9790	0.495
0.3181	0.1	30	0.3527	0.975	0.9752	0.975	0.9750	0.489
0.3134	0.1333	40	0.3602	0.971	0.9714	0.971	0.9710	0.485
0.3002	0.1667	50	0.3481	0.979	0.9790	0.979	0.9790	0.501
0.3226	0.2	60	0.3547	0.978	0.9780	0.978	0.9780	0.496
0.2919	0.2333	70	0.3687	0.972	0.9724	0.972	0.9720	0.486
0.2932	0.2667	80	0.3822	0.965	0.9664	0.965	0.9650	0.473
0.3303	0.3	90	0.3754	0.969	0.9700	0.969	0.9690	0.477
0.3162	0.3333	100	0.3557	0.975	0.9750	0.975	0.9750	0.505
0.3012	0.3667	110	0.3554	0.974	0.9741	0.974	0.9740	0.506
0.3337	0.4	120	0.3629	0.972	0.9725	0.972	0.9720	0.484
0.3007	0.4333	130	0.3492	0.979	0.9792	0.979	0.9790	0.491
0.3283	0.4667	140	0.3467	0.979	0.9790	0.979	0.9790	0.495
0.3238	0.5	150	0.3410	0.981	0.9810	0.981	0.9810	0.497
0.3076	0.5333	160	0.3387	0.982	0.9820	0.982	0.9820	0.498
0.3348	0.5667	170	0.3375	0.982	0.9820	0.982	0.9820	0.498
0.3258	0.6	180	0.3401	0.98	0.9801	0.98	0.9800	0.494
0.3195	0.6333	190	0.3424	0.978	0.9781	0.978	0.9780	0.492
0.31	0.6667	200	0.3392	0.981	0.9810	0.981	0.9810	0.495
0.3407	0.7	210	0.3393	0.982	0.9820	0.982	0.9820	0.502
0.3494	0.7333	220	0.3413	0.981	0.9810	0.981	0.9810	0.501
0.3574	0.7667	230	0.3402	0.982	0.9820	0.982	0.9820	0.496
0.3379	0.8	240	0.3385	0.982	0.9820	0.982	0.9820	0.496
0.3532	0.8333	250	0.3385	0.982	0.9820	0.982	0.9820	0.496
0.318	0.8667	260	0.3425	0.98	0.9801	0.98	0.9800	0.494
0.3475	0.9	270	0.3432	0.98	0.9801	0.98	0.9800	0.494
0.3142	0.9333	280	0.3408	0.981	0.9810	0.981	0.9810	0.495
0.3421	0.9667	290	0.3404	0.981	0.9810	0.981	0.9810	0.495
0.2935	1.0	300	0.3399	0.981	0.9810	0.981	0.9810	0.495

Framework versions

Transformers 4.41.0
Pytorch 2.3.0+cu121
Datasets 2.19.1
Tokenizers 0.19.1

Task: Text Classification
Library: transformers
Type: roberta
License: apache-2.0
Created: May 28, 2024
Updated: May 28, 2024