license: apache-2.0
base_model: projecte-aina/roberta-base-ca-v2-cased-te
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: 080524_epoch_5
results: []
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: 0.5972
- Accuracy: 0.8445
- Precision: 0.8448
- Recall: 0.8445
- F1: 0.8445
- Ratio: 0.4874
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 |
|---|---|---|---|---|---|---|---|---|
| 0.4518 | 0.1626 | 10 | 0.6633 | 0.8361 | 0.8469 | 0.8361 | 0.8348 | 0.4118 |
| 0.4418 | 0.3252 | 20 | 0.6798 | 0.8277 | 0.8279 | 0.8277 | 0.8277 | 0.5126 |
| 0.5709 | 0.4878 | 30 | 0.7447 | 0.8193 | 0.8367 | 0.8193 | 0.8170 | 0.3866 |
| 0.6645 | 0.6504 | 40 | 0.6229 | 0.8487 | 0.8487 | 0.8487 | 0.8487 | 0.5 |
| 0.6606 | 0.8130 | 50 | 0.6014 | 0.8445 | 0.8446 | 0.8445 | 0.8445 | 0.5042 |
| 0.5763 | 0.9756 | 60 | 0.5972 | 0.8445 | 0.8448 | 0.8445 | 0.8445 | 0.4874 |
precision recall f1-score top1-score top2-score top3-score good1-score good2-score support
0 Aigua 0.632 0.545 0.585 0.545 0.818 0.955 0.955 0.955 22 1 Consum, comerç i mercats 0.103 0.571 0.174 0.571 0.714 0.857 0.714 0.714 7 2 Cultura 0.500 0.750 0.600 0.750 0.750 0.750 0.750 0.750 8 3 Economia 0.211 0.500 0.296 0.500 0.875 1.000 0.875 0.875 8 4 Educació 0.438 0.636 0.519 0.636 0.818 1.000 1.000 1.000 11 5 Enllumenat públic 0.833 0.851 0.842 0.851 0.936 0.979 0.979 0.979 47 6 Esports 0.562 0.750 0.643 0.750 0.917 1.000 1.000 1.000 12 7 Habitatge 0.208 0.385 0.270 0.385 0.615 0.923 0.692 0.846 13 8 Horta 0.000 0.000 0.000 0.000 0.444 0.556 0.556 0.556 9 9 Medi ambient i jardins 0.429 0.559 0.485 0.559 0.729 0.915 0.915 0.915 59 10 Neteja de la via pública 0.686 0.238 0.353 0.238 0.505 0.772 0.762 0.762 101 11 Salut pública 0.135 0.292 0.184 0.292 0.708 0.792 0.708 0.708 24 12 Seguretat ciutadana i incivisme 0.727 0.471 0.571 0.471 0.588 0.765 0.706 0.706 34 13 Serveis socials 0.333 0.667 0.444 0.667 0.889 0.889 0.889 0.889 9 14 Tràmits 0.395 0.395 0.395 0.395 0.884 0.907 0.907 0.907 43 15 Urbanisme 0.379 0.172 0.237 0.172 0.453 0.641 0.578 0.578 64 16 Via pública i mobilitat 0.778 0.778 0.778 0.778 0.846 0.889 0.864 0.867 279
macro avg 0.432 0.504 0.434 0.504 0.735 0.858 0.815 0.824 750
weighted avg 0.610 0.557 0.559 0.557 0.739 0.853 0.825 0.829 750
accuracy 0.557
error rate 0.443
Framework versions
- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1