End of training

README.md

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+---
+license: apache-2.0
+base_model: projecte-aina/roberta-base-ca-v2-cawikitc
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: p1
+  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. -->
+
+# p1
+
+This model is a fine-tuned version of [projecte-aina/roberta-base-ca-v2-cawikitc](https://huggingface.co/projecte-aina/roberta-base-ca-v2-cawikitc) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.8254
+- Accuracy: 0.5
+- Precision: 0.25
+- Recall: 0.5
+- F1: 0.3333
+- Ratio: 1.0
+
+## 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: 2
+- seed: 47
+- 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
+- lr_scheduler_warmup_steps: 4
+- num_epochs: 2
+- label_smoothing_factor: 0.1
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     | Ratio  |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:------:|
+| 0.8263        | 0.38  | 10   | 0.8199          | 0.5      | 0.5       | 0.5    | 0.3473 | 0.0163 |
+| 0.8283        | 0.75  | 20   | 0.8389          | 0.5      | 0.25      | 0.5    | 0.3333 | 1.0    |
+| 0.8167        | 1.13  | 30   | 0.8325          | 0.5      | 0.25      | 0.5    | 0.3333 | 1.0    |
+| 0.8183        | 1.51  | 40   | 0.8228          | 0.4973   | 0.2493    | 0.4973 | 0.3321 | 0.9973 |
+| 0.8178        | 1.89  | 50   | 0.8254          | 0.5      | 0.25      | 0.5    | 0.3333 | 1.0    |
+
+
+### Framework versions
+
+- Transformers 4.38.2
+- Pytorch 2.1.0+cu121
+- Datasets 2.19.0
+- Tokenizers 0.15.2

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config.json

@@ -0,0 +1,40 @@
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