QuophyDzifa
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End of training
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README.md
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@@ -3,8 +3,6 @@ license: mit
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base_model: xlnet-base-cased
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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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model-index:
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- name: Sentiment-Analysis-Model
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results: []
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This model is a fine-tuned version of [xlnet-base-cased](https://huggingface.co/xlnet-base-cased) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.
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## Model description
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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:
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### Training results
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| Training Loss | Epoch | Step
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| 0.9619 | 5.5 | 5500 | 0.9514 | 0.491 |
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| 0.9603 | 6.0 | 6000 | 0.9638 | 0.491 |
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| 0.9671 | 6.5 | 6500 | 0.9644 | 0.4055 |
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| 0.9559 | 7.0 | 7000 | 0.9523 | 0.491 |
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| 0.957 | 7.5 | 7500 | 0.9543 | 0.491 |
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| 0.9609 | 8.0 | 8000 | 0.9501 | 0.491 |
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| 0.9629 | 8.5 | 8500 | 0.9509 | 0.491 |
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| 0.9566 | 9.0 | 9000 | 0.9514 | 0.491 |
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| 0.9512 | 9.5 | 9500 | 0.9571 | 0.491 |
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| 0.9625 | 10.0 | 10000 | 0.9507 | 0.491 |
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| 0.9601 | 10.5 | 10500 | 0.9507 | 0.491 |
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| 0.9546 | 11.0 | 11000 | 0.9543 | 0.491 |
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| 0.9522 | 11.5 | 11500 | 0.8102 | 0.491 |
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| 0.8465 | 12.0 | 12000 | 0.7341 | 0.7125 |
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| 0.7581 | 12.5 | 12500 | 0.7503 | 0.7105 |
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| 0.7658 | 13.0 | 13000 | 0.7329 | 0.714 |
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| 0.7507 | 13.5 | 13500 | 0.7322 | 0.7135 |
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| 0.7422 | 14.0 | 14000 | 0.7539 | 0.7145 |
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| 0.7413 | 14.5 | 14500 | 0.7215 | 0.7135 |
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| 0.7232 | 15.0 | 15000 | 0.7255 | 0.7125 |
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### Framework versions
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base_model: xlnet-base-cased
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tags:
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- generated_from_trainer
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model-index:
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- name: Sentiment-Analysis-Model
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results: []
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This model is a fine-tuned version of [xlnet-base-cased](https://huggingface.co/xlnet-base-cased) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.7202
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- F1 Score: 0.6921
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## Model description
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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: 5
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | F1 Score |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 0.8571 | 0.5 | 500 | 0.7520 | 0.6771 |
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| 0.7848 | 1.0 | 1000 | 0.7468 | 0.6780 |
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| 0.8367 | 1.5 | 1500 | 0.8781 | 0.5579 |
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| 0.8949 | 2.0 | 2000 | 0.8666 | 0.5704 |
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| 0.7922 | 2.5 | 2500 | 0.7379 | 0.6738 |
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| 0.748 | 3.0 | 3000 | 0.7218 | 0.6833 |
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| 0.7604 | 3.5 | 3500 | 0.7853 | 0.6645 |
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| 0.7704 | 4.0 | 4000 | 0.7281 | 0.6867 |
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| 0.7562 | 4.5 | 4500 | 0.7265 | 0.6904 |
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| 0.7195 | 5.0 | 5000 | 0.7202 | 0.6921 |
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### Framework versions
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