metadata

license: apache-2.0
base_model: PlanTL-GOB-ES/roberta-base-bne
tags:
  - generated_from_trainer
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: roberta-base-bne-ner
    results: []

roberta-base-bne-ner

This model is a fine-tuned version of PlanTL-GOB-ES/roberta-base-bne on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.3159
Precision: 0.8517
Recall: 0.8933
F1: 0.8720
Accuracy: 0.9384

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: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 15

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	280	0.3006	0.7961	0.8563	0.8251	0.9164
0.4008	2.0	560	0.2984	0.7918	0.8622	0.8255	0.9203
0.4008	3.0	840	0.2324	0.8401	0.8563	0.8481	0.9343
0.1014	4.0	1120	0.2394	0.8242	0.8889	0.8553	0.9414
0.1014	5.0	1400	0.2674	0.8469	0.8933	0.8695	0.9371
0.0435	6.0	1680	0.2815	0.8255	0.8830	0.8533	0.9375
0.0435	7.0	1960	0.2713	0.8516	0.8844	0.8677	0.9444
0.0233	8.0	2240	0.2745	0.8541	0.8933	0.8733	0.9437
0.0177	9.0	2520	0.3383	0.8336	0.8978	0.8645	0.9350
0.0177	10.0	2800	0.2858	0.8606	0.8963	0.8781	0.9419
0.013	11.0	3080	0.2956	0.8350	0.8919	0.8625	0.9403
0.013	12.0	3360	0.3097	0.8423	0.9022	0.8712	0.9380
0.0104	13.0	3640	0.3158	0.8443	0.8919	0.8674	0.9380
0.0104	14.0	3920	0.3171	0.8493	0.8933	0.8708	0.9387
0.0088	15.0	4200	0.3159	0.8517	0.8933	0.8720	0.9384

Framework versions

Transformers 4.41.1
Pytorch 2.3.0+cu121
Datasets 2.19.1
Tokenizers 0.19.1