End of training
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README.md
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---
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license: apache-2.0
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base_model: projecte-aina/roberta-base-ca-v2
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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: FS_27_06
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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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# FS_27_06
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This model is a fine-tuned version of [projecte-aina/roberta-base-ca-v2](https://huggingface.co/projecte-aina/roberta-base-ca-v2) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1516
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- Accuracy: 0.966
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- Precision: 0.9675
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- Recall: 0.966
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- F1: 0.9661
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## Model description
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More information needed
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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: 5e-05
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- train_batch_size: 8
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- eval_batch_size: 8
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- seed: 42
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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_steps: 500
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- num_epochs: 5
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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| 1.7152 | 1.0 | 375 | 1.5745 | 0.94 | 0.9430 | 0.9400 | 0.9403 |
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| 0.2064 | 2.0 | 750 | 0.2286 | 0.964 | 0.9657 | 0.9640 | 0.9643 |
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| 0.1779 | 3.0 | 1125 | 0.1743 | 0.966 | 0.9670 | 0.9660 | 0.9661 |
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| 0.0208 | 4.0 | 1500 | 0.1547 | 0.966 | 0.9672 | 0.9660 | 0.9659 |
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| 0.0166 | 5.0 | 1875 | 0.1516 | 0.966 | 0.9675 | 0.966 | 0.9661 |
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### Framework versions
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- Transformers 4.41.0
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- Pytorch 2.3.0+cu121
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- Datasets 2.19.1
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- Tokenizers 0.19.1
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