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---
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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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- f1
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model-index:
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- name: twitter-xlm-roberta-base-sentiment-finetunned-davincis-local
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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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# twitter-xlm-roberta-base-sentiment-finetunned-davincis-local
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This model is a fine-tuned version of [citizenlab/twitter-xlm-roberta-base-sentiment-finetunned](https://huggingface.co/citizenlab/twitter-xlm-roberta-base-sentiment-finetunned) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.5461
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- Accuracy: 0.9302
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- F1: 0.9301
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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: 2e-05
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- train_batch_size: 72
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- eval_batch_size: 72
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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 |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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| 0.4006 | 1.0 | 41 | 0.3037 | 0.8779 | 0.8771 |
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| 0.2165 | 2.0 | 82 | 0.2007 | 0.9205 | 0.9205 |
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| 0.1311 | 3.0 | 123 | 0.2124 | 0.9244 | 0.9244 |
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| 0.0839 | 4.0 | 164 | 0.2504 | 0.9341 | 0.9341 |
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| 0.0525 | 5.0 | 205 | 0.3695 | 0.9147 | 0.9144 |
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| 0.0392 | 6.0 | 246 | 0.3393 | 0.9244 | 0.9243 |
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| 0.0282 | 7.0 | 287 | 0.4203 | 0.9244 | 0.9242 |
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| 0.0205 | 8.0 | 328 | 0.3889 | 0.9302 | 0.9301 |
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| 0.012 | 9.0 | 369 | 0.6586 | 0.9012 | 0.9006 |
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| 0.0069 | 10.0 | 410 | 0.4873 | 0.9302 | 0.9301 |
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| 0.005 | 11.0 | 451 | 0.6105 | 0.9089 | 0.9085 |
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| 0.0082 | 12.0 | 492 | 0.4642 | 0.9302 | 0.9301 |
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| 0.0022 | 13.0 | 533 | 0.3709 | 0.9516 | 0.9515 |
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| 0.0088 | 14.0 | 574 | 0.5322 | 0.9283 | 0.9281 |
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| 0.0067 | 15.0 | 615 | 0.6661 | 0.9128 | 0.9124 |
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| 0.0015 | 16.0 | 656 | 0.5450 | 0.9283 | 0.9282 |
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| 0.0006 | 17.0 | 697 | 0.5453 | 0.9302 | 0.9301 |
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| 0.0002 | 18.0 | 738 | 0.5555 | 0.9302 | 0.9301 |
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| 0.0018 | 19.0 | 779 | 0.5408 | 0.9302 | 0.9301 |
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| 0.0022 | 20.0 | 820 | 0.5461 | 0.9302 | 0.9301 |
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### Framework versions
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- Transformers 4.27.4
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- Pytorch 1.13.1+cu116
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- Datasets 2.11.0
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- Tokenizers 0.13.2
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