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my-model-Bertin-Area

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lBober/my-model-bertin-Area

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  1. README.md +34 -18
  2. model.safetensors +1 -1
  3. runs/May25_21-14-04_54438e66731d/events.out.tfevents.1716671645.54438e66731d.35912.0 +3 -0
  4. training_args.bin +1 -1
README.md CHANGED
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  - generated_from_trainer
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  metrics:
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  - accuracy
 
 
 
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  model-index:
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  - name: my-model-Bertin-Area
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  results: []
@@ -17,8 +20,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [bertin-project/bertin-roberta-base-spanish](https://huggingface.co/bertin-project/bertin-roberta-base-spanish) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.5347
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- - Accuracy: 0.3885
 
 
 
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  ## Model description
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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: 100
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- - eval_batch_size: 100
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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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- - num_epochs: 10
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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- |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | 1.8826 | 1.0 | 7 | 1.7742 | 0.2590 |
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- | 1.6982 | 2.0 | 14 | 1.7521 | 0.2806 |
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- | 1.6317 | 3.0 | 21 | 1.6768 | 0.3022 |
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- | 1.5322 | 4.0 | 28 | 1.6329 | 0.3597 |
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- | 1.3803 | 5.0 | 35 | 1.6064 | 0.3597 |
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- | 1.2126 | 6.0 | 42 | 1.5785 | 0.3813 |
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- | 1.072 | 7.0 | 49 | 1.5532 | 0.3885 |
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- | 0.9604 | 8.0 | 56 | 1.5330 | 0.3885 |
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- | 0.876 | 9.0 | 63 | 1.5345 | 0.3957 |
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- | 0.8119 | 10.0 | 70 | 1.5347 | 0.3885 |
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  - generated_from_trainer
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  metrics:
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  - accuracy
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+ - f1
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+ - precision
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+ - recall
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  model-index:
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  - name: my-model-Bertin-Area
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  results: []
 
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  This model is a fine-tuned version of [bertin-project/bertin-roberta-base-spanish](https://huggingface.co/bertin-project/bertin-roberta-base-spanish) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 2.0387
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+ - Accuracy: 0.6403
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+ - F1: 0.6388
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+ - Precision: 0.6549
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+ - Recall: 0.6403
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  ## Model description
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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: 30
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+ - eval_batch_size: 5
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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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+ - num_epochs: 20
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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+ | 1.7851 | 1.0 | 22 | 1.7324 | 0.3381 | 0.2327 | 0.3338 | 0.3381 |
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+ | 1.6204 | 2.0 | 44 | 1.6785 | 0.3165 | 0.2082 | 0.2941 | 0.3165 |
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+ | 1.3964 | 3.0 | 66 | 1.4346 | 0.5036 | 0.4611 | 0.4823 | 0.5036 |
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+ | 0.9218 | 4.0 | 88 | 1.2695 | 0.5612 | 0.5181 | 0.4952 | 0.5612 |
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+ | 0.4872 | 5.0 | 110 | 1.3801 | 0.6043 | 0.5794 | 0.5676 | 0.6043 |
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+ | 0.2341 | 6.0 | 132 | 1.3891 | 0.6115 | 0.5997 | 0.5910 | 0.6115 |
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+ | 0.123 | 7.0 | 154 | 1.4263 | 0.6259 | 0.6070 | 0.6180 | 0.6259 |
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+ | 0.0737 | 8.0 | 176 | 1.6080 | 0.6331 | 0.6214 | 0.6336 | 0.6331 |
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+ | 0.038 | 9.0 | 198 | 1.6996 | 0.6187 | 0.6075 | 0.6016 | 0.6187 |
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+ | 0.0278 | 10.0 | 220 | 1.8417 | 0.6475 | 0.6446 | 0.6595 | 0.6475 |
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+ | 0.0142 | 11.0 | 242 | 1.7940 | 0.6547 | 0.6543 | 0.6737 | 0.6547 |
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+ | 0.0085 | 12.0 | 264 | 1.9102 | 0.6187 | 0.6142 | 0.6273 | 0.6187 |
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+ | 0.0035 | 13.0 | 286 | 1.9572 | 0.6403 | 0.6414 | 0.6647 | 0.6403 |
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+ | 0.0024 | 14.0 | 308 | 1.9346 | 0.6475 | 0.6441 | 0.6568 | 0.6475 |
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+ | 0.0021 | 15.0 | 330 | 1.9751 | 0.6475 | 0.6436 | 0.6606 | 0.6475 |
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+ | 0.0017 | 16.0 | 352 | 2.0226 | 0.6547 | 0.6519 | 0.6687 | 0.6547 |
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+ | 0.0016 | 17.0 | 374 | 2.0257 | 0.6475 | 0.6458 | 0.6629 | 0.6475 |
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+ | 0.0015 | 18.0 | 396 | 2.0326 | 0.6403 | 0.6388 | 0.6549 | 0.6403 |
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+ | 0.0014 | 19.0 | 418 | 2.0369 | 0.6403 | 0.6388 | 0.6549 | 0.6403 |
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+ | 0.0014 | 20.0 | 440 | 2.0387 | 0.6403 | 0.6388 | 0.6549 | 0.6403 |
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  ### Framework versions
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