metadata

license: mit
base_model: FacebookAI/xlm-roberta-base
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - precision
  - recall
  - f1
model-index:
  - name: soluciona_fm_tcv_1
    results: []

mapping

'Accessibilitat': 0,
'Arbrat': 1,
'Desguassos i embornals': 2,
'Enllumenat públic': 3,
'Escombraries acumulades': 4,
'Fuites d\'aigua': 5,
'Grafits': 6,
'Mobiliari urbà': 7,
'Obres inacabades': 8,
'Parcs i jardins': 9,
'Plagues': 10,
'Senyalització vial': 11,
'Sorolls': 12,
'Sots a la calçada': 13,
'Vehicles abandonats': 14,
'Voreres danyades': 15

soluciona_fm_tcv_1

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

Loss: 0.0260
Accuracy: 0.996
Precision: 0.9962
Recall: 0.9960
F1: 0.9960

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: 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: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
0.9405	1.0	675	0.1074	0.978	0.9793	0.9778	0.9780
0.106	2.0	1350	0.0876	0.986	0.9866	0.9861	0.9860
0.0237	3.0	2025	0.0491	0.992	0.9923	0.9920	0.9920
0.0181	4.0	2700	0.0620	0.988	0.9897	0.9879	0.9880
0.0206	5.0	3375	0.0332	0.994	0.9943	0.9940	0.9940
0.0071	6.0	4050	0.0260	0.996	0.9962	0.9960	0.9960
0.0012	7.0	4725	0.0416	0.996	0.9962	0.9960	0.9960
0.009	8.0	5400	0.0723	0.994	0.9943	0.9940	0.9940
0.0001	9.0	6075	0.0447	0.996	0.9962	0.9960	0.9960
0.0001	10.0	6750	0.0469	0.996	0.9962	0.9960	0.9960

Framework versions

Transformers 4.41.2
Pytorch 2.3.0+cu121
Datasets 2.20.0
Tokenizers 0.19.1