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--- |
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license: apache-2.0 |
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base_model: projecte-aina/roberta-base-ca-v2-cased-te |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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- precision |
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- recall |
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- f1 |
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model-index: |
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- name: 2504v1 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# 2504v1 |
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This model is a fine-tuned version of [projecte-aina/roberta-base-ca-v2-cased-te](https://huggingface.co/projecte-aina/roberta-base-ca-v2-cased-te) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5947 |
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- Accuracy: 0.8655 |
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- Precision: 0.8655 |
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- Recall: 0.8655 |
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- F1: 0.8655 |
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- Ratio: 0.5 |
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## Model description |
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Punto, change label 6 |
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-------TRAIN------- |
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Proporción de etiquetas en el conjunto de datos: |
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Aigua: 36 muestras (5.88%) |
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Consum, comerç i mercats: 36 muestras (5.88%) |
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Cultura: 36 muestras (5.88%) |
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Economia: 36 muestras (5.88%) |
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Educació: 36 muestras (5.88%) |
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Enllumenat públic: 36 muestras (5.88%) |
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Esports: 36 muestras (5.88%) |
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Habitatge: 36 muestras (5.88%) |
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Horta: 36 muestras (5.88%) |
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Medi ambient i jardins: 36 muestras (5.88%) |
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Neteja de la via pública: 36 muestras (5.88%) |
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Salut pública: 36 muestras (5.88%) |
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Seguretat ciutadana i incivisme: 36 muestras (5.88%) |
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Serveis socials: 36 muestras (5.88%) |
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Tràmits: 36 muestras (5.88%) |
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Urbanisme: 36 muestras (5.88%) |
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Via pública i mobilitat: 36 muestras (5.88%) |
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-------VAL------- |
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Proporción de etiquetas en el conjunto de datos: |
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Aigua: 7 muestras (5.88%) |
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Consum, comerç i mercats: 7 muestras (5.88%) |
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Cultura: 7 muestras (5.88%) |
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Economia: 7 muestras (5.88%) |
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Educació: 7 muestras (5.88%) |
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Enllumenat públic: 7 muestras (5.88%) |
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Esports: 7 muestras (5.88%) |
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Habitatge: 7 muestras (5.88%) |
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Horta: 7 muestras (5.88%) |
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Medi ambient i jardins: 7 muestras (5.88%) |
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Neteja de la via pública: 7 muestras (5.88%) |
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Salut pública: 7 muestras (5.88%) |
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Seguretat ciutadana i incivisme: 7 muestras (5.88%) |
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Serveis socials: 7 muestras (5.88%) |
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Tràmits: 7 muestras (5.88%) |
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Urbanisme: 7 muestras (5.88%) |
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Via pública i mobilitat: 7 muestras (5.88%) |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 32 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.06 |
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- lr_scheduler_warmup_steps: 4 |
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- num_epochs: 10 |
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- label_smoothing_factor: 0.1 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Ratio | |
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|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:------:| |
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| 3.6209 | 0.2597 | 10 | 1.6277 | 0.5462 | 0.5476 | 0.5462 | 0.5430 | 0.4160 | |
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| 1.4156 | 0.5195 | 20 | 1.0896 | 0.5588 | 0.5620 | 0.5588 | 0.5531 | 0.6134 | |
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| 1.0016 | 0.7792 | 30 | 0.9251 | 0.5504 | 0.6083 | 0.5504 | 0.4811 | 0.8655 | |
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| 0.9148 | 1.0390 | 40 | 0.8180 | 0.6765 | 0.6912 | 0.6765 | 0.6701 | 0.3613 | |
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| 0.7958 | 1.2987 | 50 | 0.7074 | 0.7983 | 0.8038 | 0.7983 | 0.7974 | 0.5672 | |
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| 0.7218 | 1.5584 | 60 | 0.6919 | 0.8025 | 0.8216 | 0.8025 | 0.7995 | 0.6218 | |
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| 0.7019 | 1.8182 | 70 | 0.6693 | 0.8277 | 0.8383 | 0.8277 | 0.8264 | 0.4118 | |
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| 0.6805 | 2.0779 | 80 | 0.6229 | 0.8193 | 0.8232 | 0.8193 | 0.8188 | 0.5546 | |
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| 0.6206 | 2.3377 | 90 | 0.5833 | 0.8655 | 0.8665 | 0.8655 | 0.8655 | 0.4748 | |
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| 0.5979 | 2.5974 | 100 | 0.5642 | 0.8613 | 0.8614 | 0.8613 | 0.8613 | 0.5042 | |
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| 0.6115 | 2.8571 | 110 | 0.5634 | 0.8613 | 0.8614 | 0.8613 | 0.8613 | 0.5042 | |
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| 0.6016 | 3.1169 | 120 | 0.5447 | 0.8655 | 0.8665 | 0.8655 | 0.8655 | 0.5252 | |
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| 0.5514 | 3.3766 | 130 | 0.5601 | 0.8571 | 0.8588 | 0.8571 | 0.8570 | 0.5336 | |
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| 0.4678 | 3.6364 | 140 | 0.5717 | 0.8445 | 0.8475 | 0.8445 | 0.8442 | 0.5462 | |
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| 0.4962 | 3.8961 | 150 | 0.5684 | 0.8571 | 0.8575 | 0.8571 | 0.8571 | 0.5168 | |
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| 0.5214 | 4.1558 | 160 | 0.5573 | 0.8529 | 0.8536 | 0.8529 | 0.8529 | 0.5210 | |
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| 0.4962 | 4.4156 | 170 | 0.5686 | 0.8445 | 0.8475 | 0.8445 | 0.8442 | 0.5462 | |
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| 0.5032 | 4.6753 | 180 | 0.5525 | 0.8613 | 0.8616 | 0.8613 | 0.8613 | 0.4874 | |
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| 0.4593 | 4.9351 | 190 | 0.5747 | 0.8571 | 0.8581 | 0.8571 | 0.8571 | 0.5252 | |
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| 0.4335 | 5.1948 | 200 | 0.5919 | 0.8487 | 0.8488 | 0.8487 | 0.8487 | 0.5084 | |
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| 0.5023 | 5.4545 | 210 | 0.5854 | 0.8613 | 0.8626 | 0.8613 | 0.8612 | 0.4706 | |
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| 0.4399 | 5.7143 | 220 | 0.5728 | 0.8697 | 0.8719 | 0.8697 | 0.8696 | 0.5378 | |
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| 0.4182 | 5.9740 | 230 | 0.5737 | 0.8655 | 0.8665 | 0.8655 | 0.8655 | 0.5252 | |
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| 0.4337 | 6.2338 | 240 | 0.6013 | 0.8529 | 0.8536 | 0.8529 | 0.8529 | 0.5210 | |
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| 0.4046 | 6.4935 | 250 | 0.6200 | 0.8571 | 0.8575 | 0.8571 | 0.8571 | 0.5168 | |
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| 0.4304 | 6.7532 | 260 | 0.6106 | 0.8697 | 0.8698 | 0.8697 | 0.8697 | 0.5042 | |
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| 0.45 | 7.0130 | 270 | 0.6154 | 0.8655 | 0.8681 | 0.8655 | 0.8653 | 0.4580 | |
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| 0.3687 | 7.2727 | 280 | 0.6109 | 0.8655 | 0.8655 | 0.8655 | 0.8655 | 0.5 | |
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| 0.4102 | 7.5325 | 290 | 0.6118 | 0.8529 | 0.8536 | 0.8529 | 0.8529 | 0.5210 | |
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| 0.4197 | 7.7922 | 300 | 0.5969 | 0.8655 | 0.8656 | 0.8655 | 0.8655 | 0.4916 | |
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| 0.4874 | 8.0519 | 310 | 0.5794 | 0.8655 | 0.8656 | 0.8655 | 0.8655 | 0.4916 | |
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| 0.3694 | 8.3117 | 320 | 0.5777 | 0.8697 | 0.8704 | 0.8697 | 0.8697 | 0.5210 | |
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| 0.4029 | 8.5714 | 330 | 0.5828 | 0.8697 | 0.8700 | 0.8697 | 0.8697 | 0.5126 | |
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| 0.3946 | 8.8312 | 340 | 0.5860 | 0.8697 | 0.8698 | 0.8697 | 0.8697 | 0.5042 | |
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| 0.3991 | 9.0909 | 350 | 0.5864 | 0.8655 | 0.8655 | 0.8655 | 0.8655 | 0.5 | |
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| 0.3707 | 9.3506 | 360 | 0.5918 | 0.8697 | 0.8698 | 0.8697 | 0.8697 | 0.5042 | |
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| 0.3821 | 9.6104 | 370 | 0.5943 | 0.8655 | 0.8655 | 0.8655 | 0.8655 | 0.5 | |
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| 0.4135 | 9.8701 | 380 | 0.5947 | 0.8655 | 0.8655 | 0.8655 | 0.8655 | 0.5 | |
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### Framework versions |
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- Transformers 4.40.0 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.19.0 |
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- Tokenizers 0.19.1 |
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