End of training

README.md

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+---
+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: 2504separado5
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# 2504separado5
+
+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.
+It achieves the following results on the evaluation set:
+- Loss: 0.6571
+- Accuracy: 0.8487
+- Precision: 0.8491
+- Recall: 0.8487
+- F1: 0.8487
+- Ratio: 0.5168
+
+## 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: 16
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 32
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.06
+- num_epochs: 4
+- label_smoothing_factor: 0.1
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Accuracy | Precision | Recall | F1     | Ratio  |
+|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:------:|
+| 0.3101        | 0.9870 | 38   | 0.7275          | 0.8445   | 0.8465    | 0.8445 | 0.8443 | 0.4622 |
+| 0.3189        | 2.0    | 77   | 0.7399          | 0.8445   | 0.8448    | 0.8445 | 0.8445 | 0.5126 |
+| 0.3786        | 2.9870 | 115  | 0.7200          | 0.8361   | 0.8390    | 0.8361 | 0.8358 | 0.5462 |
+| 0.3816        | 3.9481 | 152  | 0.6571          | 0.8487   | 0.8491    | 0.8487 | 0.8487 | 0.5168 |
+
+
+### Framework versions
+
+- Transformers 4.40.0
+- Pytorch 2.2.1+cu121
+- Datasets 2.19.0
+- Tokenizers 0.19.1

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