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my-model-SaBERT-Area

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lBober/my-model-SaBERT-Area

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  1. README.md +26 -26
  2. model.safetensors +1 -1
  3. runs/May27_07-42-07_ebad249b5c71/events.out.tfevents.1716795728.ebad249b5c71.1052.0 +3 -0
  4. training_args.bin +1 -1
README.md CHANGED
@@ -1,8 +1,8 @@
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  ---
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  license: apache-2.0
 
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  tags:
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  - generated_from_trainer
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- base_model: VerificadoProfesional/SaBERT-Spanish-Sentiment-Analysis
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  metrics:
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  - accuracy
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  - f1
@@ -20,11 +20,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [VerificadoProfesional/SaBERT-Spanish-Sentiment-Analysis](https://huggingface.co/VerificadoProfesional/SaBERT-Spanish-Sentiment-Analysis) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 2.4198
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- - Accuracy: 0.5827
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- - F1: 0.5811
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- - Precision: 0.5930
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- - Recall: 0.5827
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  ## Model description
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@@ -55,26 +55,26 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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- | 1.6646 | 1.0 | 22 | 1.4593 | 0.4245 | 0.3572 | 0.3697 | 0.4245 |
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- | 1.1922 | 2.0 | 44 | 1.4048 | 0.4748 | 0.4073 | 0.3990 | 0.4748 |
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- | 0.7828 | 3.0 | 66 | 1.3378 | 0.5324 | 0.5319 | 0.5646 | 0.5324 |
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- | 0.3633 | 4.0 | 88 | 1.4701 | 0.5612 | 0.5515 | 0.5619 | 0.5612 |
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- | 0.1526 | 5.0 | 110 | 1.6265 | 0.5612 | 0.5543 | 0.5623 | 0.5612 |
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- | 0.0543 | 6.0 | 132 | 1.8798 | 0.5180 | 0.5308 | 0.5648 | 0.5180 |
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- | 0.0651 | 7.0 | 154 | 2.0452 | 0.5324 | 0.5428 | 0.5958 | 0.5324 |
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- | 0.0248 | 8.0 | 176 | 2.1915 | 0.5180 | 0.5294 | 0.5843 | 0.5180 |
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- | 0.0146 | 9.0 | 198 | 2.2572 | 0.5108 | 0.5017 | 0.5256 | 0.5108 |
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- | 0.0048 | 10.0 | 220 | 2.3240 | 0.5540 | 0.5486 | 0.5747 | 0.5540 |
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- | 0.0035 | 11.0 | 242 | 2.2480 | 0.5612 | 0.5589 | 0.5713 | 0.5612 |
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- | 0.0028 | 12.0 | 264 | 2.2854 | 0.5612 | 0.5579 | 0.5719 | 0.5612 |
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- | 0.0025 | 13.0 | 286 | 2.3299 | 0.5612 | 0.5601 | 0.5763 | 0.5612 |
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- | 0.0022 | 14.0 | 308 | 2.3602 | 0.5612 | 0.5575 | 0.5732 | 0.5612 |
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- | 0.002 | 15.0 | 330 | 2.3759 | 0.5755 | 0.5726 | 0.5851 | 0.5755 |
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- | 0.0019 | 16.0 | 352 | 2.3880 | 0.5827 | 0.5811 | 0.5930 | 0.5827 |
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- | 0.0019 | 17.0 | 374 | 2.4072 | 0.5755 | 0.5726 | 0.5851 | 0.5755 |
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- | 0.0018 | 18.0 | 396 | 2.4125 | 0.5755 | 0.5726 | 0.5851 | 0.5755 |
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- | 0.0018 | 19.0 | 418 | 2.4185 | 0.5755 | 0.5726 | 0.5851 | 0.5755 |
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- | 0.0017 | 20.0 | 440 | 2.4198 | 0.5827 | 0.5811 | 0.5930 | 0.5827 |
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  ### Framework versions
 
1
  ---
2
  license: apache-2.0
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+ base_model: VerificadoProfesional/SaBERT-Spanish-Sentiment-Analysis
4
  tags:
5
  - generated_from_trainer
 
6
  metrics:
7
  - accuracy
8
  - f1
 
20
 
21
  This model is a fine-tuned version of [VerificadoProfesional/SaBERT-Spanish-Sentiment-Analysis](https://huggingface.co/VerificadoProfesional/SaBERT-Spanish-Sentiment-Analysis) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 2.6448
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+ - Accuracy: 0.5613
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+ - F1: 0.5575
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+ - Precision: 0.5778
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+ - Recall: 0.5613
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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+ | 1.6981 | 1.0 | 25 | 1.4370 | 0.4581 | 0.4302 | 0.5630 | 0.4581 |
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+ | 1.2551 | 2.0 | 50 | 1.3700 | 0.4839 | 0.4474 | 0.4963 | 0.4839 |
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+ | 0.6886 | 3.0 | 75 | 1.4792 | 0.5161 | 0.5075 | 0.5181 | 0.5161 |
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+ | 0.307 | 4.0 | 100 | 1.8805 | 0.4645 | 0.4496 | 0.4942 | 0.4645 |
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+ | 0.1402 | 5.0 | 125 | 1.8803 | 0.5290 | 0.5170 | 0.5171 | 0.5290 |
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+ | 0.0695 | 6.0 | 150 | 2.3137 | 0.5161 | 0.5016 | 0.5416 | 0.5161 |
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+ | 0.0376 | 7.0 | 175 | 2.1753 | 0.5548 | 0.5444 | 0.5536 | 0.5548 |
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+ | 0.0167 | 8.0 | 200 | 2.2900 | 0.5677 | 0.5566 | 0.5645 | 0.5677 |
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+ | 0.0089 | 9.0 | 225 | 2.4479 | 0.5419 | 0.5379 | 0.5652 | 0.5419 |
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+ | 0.0041 | 10.0 | 250 | 2.7057 | 0.5290 | 0.5256 | 0.5645 | 0.5290 |
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+ | 0.0034 | 11.0 | 275 | 2.5117 | 0.5677 | 0.5635 | 0.5727 | 0.5677 |
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+ | 0.0026 | 12.0 | 300 | 2.5989 | 0.5484 | 0.5437 | 0.5601 | 0.5484 |
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+ | 0.0022 | 13.0 | 325 | 2.5452 | 0.5677 | 0.5678 | 0.5890 | 0.5677 |
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+ | 0.002 | 14.0 | 350 | 2.5804 | 0.5548 | 0.5515 | 0.5717 | 0.5548 |
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+ | 0.0018 | 15.0 | 375 | 2.6138 | 0.5548 | 0.5504 | 0.5672 | 0.5548 |
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+ | 0.0017 | 16.0 | 400 | 2.5942 | 0.5548 | 0.5504 | 0.5672 | 0.5548 |
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+ | 0.0017 | 17.0 | 425 | 2.6194 | 0.5613 | 0.5568 | 0.5743 | 0.5613 |
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+ | 0.0016 | 18.0 | 450 | 2.6354 | 0.5613 | 0.5568 | 0.5743 | 0.5613 |
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+ | 0.0015 | 19.0 | 475 | 2.6417 | 0.5613 | 0.5568 | 0.5743 | 0.5613 |
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+ | 0.0015 | 20.0 | 500 | 2.6448 | 0.5613 | 0.5575 | 0.5778 | 0.5613 |
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  ### Framework versions
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