Bert_TPF_v10

JhonMR/Bert_TPF_v10

Bert_TPF_v10 is a text classification model from JhonMR. 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: bert
Access: Public
Created: Oct 30, 2024
Updated: Oct 30, 2024
SHA: eac17a9a

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Base models

dccuchile/bert-base-spanish-wwm-uncased

Model card

From the Hugging Face model README

Bert_TPF_v10

This model is a fine-tuned version of dccuchile/bert-base-spanish-wwm-uncased on the None dataset. It achieves the following results on the evaluation set:

Accuracy@en: 0.8315
F1@en: 0.8323
Precision@en: 0.8373
Recall@en: 0.8368
Loss@en: 0.6173
Loss: 0.6173

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: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_steps: 500
num_epochs: 20

Training results

Training Loss	Epoch	Step	Accuracy@en	F1@en	Precision@en	Recall@en	Loss@en	Validation Loss
3.2405	1.0	552	0.2037	0.1306	0.1465	0.2065	2.5934	2.5934
2.3891	2.0	1104	0.2992	0.2349	0.2586	0.3058	2.0876	2.0876
2.0117	3.0	1656	0.3765	0.3448	0.3683	0.3839	1.8638	1.8638
1.7804	4.0	2208	0.4619	0.4287	0.4433	0.4705	1.6337	1.6337
1.4913	5.0	2760	0.5228	0.4905	0.5357	0.5306	1.3950	1.3950
1.2177	6.0	3312	0.5696	0.5529	0.6054	0.5773	1.2562	1.2562
1.0274	7.0	3864	0.6278	0.6086	0.6598	0.6360	1.0466	1.0466
0.8372	8.0	4416	0.7050	0.7007	0.7254	0.7104	0.8734	0.8734
0.67	9.0	4968	0.7407	0.7373	0.7510	0.7463	0.8112	0.8112
0.5259	10.0	5520	0.8	0.7999	0.8069	0.8050	0.6594	0.6594
0.4333	11.0	6072	0.8095	0.8056	0.8219	0.8159	0.6305	0.6305
0.3503	12.0	6624	0.8019	0.7985	0.8132	0.8074	0.6698	0.6698
0.2961	13.0	7176	0.8315	0.8323	0.8373	0.8368	0.6173	0.6173
0.2441	14.0	7728	0.8450	0.8459	0.8482	0.8493	0.6287	0.6287
0.2078	15.0	8280	0.8471	0.8477	0.8508	0.8511	0.6280	0.6280
0.1857	16.0	8832	0.8463	0.8470	0.8513	0.8510	0.6293	0.6293
0.164	17.0	9384	0.8471	0.8480	0.8510	0.8512	0.6371	0.6371
0.1467	18.0	9936	0.8489	0.8497	0.8536	0.8532	0.6410	0.6410
0.1409	19.0	10488	0.8489	0.8496	0.8535	0.8528	0.6396	0.6396
0.1378	20.0	11040	0.8497	0.8505	0.8543	0.8537	0.6395	0.6395

Framework versions

Transformers 4.44.2
Pytorch 2.5.0+cu121
Datasets 3.0.2
Tokenizers 0.19.1

Task: Text Classification
Library: transformers
Type: bert
Created: Oct 30, 2024
Updated: Oct 30, 2024