M4rt0no/Priorizacion_v2_batch32

Gestionabilidad-v2_batch32

This model is a fine-tuned version of dccuchile/tulio-chilean-spanish-bert on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.8143
• Accuracy: 0.8451
• Precision: 0.8438
• Recall: 0.8451
• F1: 0.8443

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: 5e-05
• train_batch_size: 32
• eval_batch_size: 8
• seed: 42
• optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
0.5652	0.4292	400	0.5002	0.8044	0.8041	0.8044	0.8037
0.4494	0.8584	800	0.4102	0.8337	0.8341	0.8337	0.8338
0.3439	1.2876	1200	0.4437	0.8268	0.8427	0.8268	0.8286
0.3099	1.7167	1600	0.4289	0.8369	0.8387	0.8369	0.8375
0.26	2.1459	2000	0.4758	0.8405	0.8422	0.8405	0.8413
0.1838	2.5751	2400	0.5046	0.8384	0.8416	0.8384	0.8388
0.1733	3.0043	2800	0.4968	0.8378	0.8390	0.8378	0.8371
0.0997	3.4335	3200	0.6251	0.8412	0.8397	0.8412	0.8403
0.102	3.8627	3600	0.6324	0.8496	0.8504	0.8496	0.8499
0.0719	4.2918	4000	0.7935	0.8455	0.8463	0.8455	0.8449
0.0576	4.7210	4400	0.8143	0.8451	0.8438	0.8451	0.8443

Framework versions

• Transformers 4.48.3
• Pytorch 2.5.1+cu124
• Datasets 3.3.2
• Tokenizers 0.21.0