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--- |
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base_model: cardiffnlp/twitter-xlm-roberta-base-sentiment |
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metrics: |
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- precision |
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- recall |
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- f1 |
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- accuracy |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: fineTuningXLMRoberta-TokenClassification-latest |
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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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# fineTuningXLMRoberta-TokenClassification-latest |
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This model is a fine-tuned version of [cardiffnlp/twitter-xlm-roberta-base-sentiment](https://huggingface.co/cardiffnlp/twitter-xlm-roberta-base-sentiment) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8366 |
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- Precision: 0.1689 |
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- Recall: 0.1683 |
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- F1: 0.1686 |
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- Accuracy: 0.6766 |
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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: 32 |
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- eval_batch_size: 32 |
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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: 15 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
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| No log | 1.0 | 33 | 0.7181 | 0.1472 | 0.1219 | 0.1333 | 0.6725 | |
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| No log | 2.0 | 66 | 0.7405 | 0.1414 | 0.1644 | 0.1521 | 0.6716 | |
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| No log | 3.0 | 99 | 0.6809 | 0.1694 | 0.1393 | 0.1529 | 0.6976 | |
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| No log | 4.0 | 132 | 0.7435 | 0.1216 | 0.1393 | 0.1298 | 0.6450 | |
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| No log | 5.0 | 165 | 0.7392 | 0.1709 | 0.1431 | 0.1558 | 0.6904 | |
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| No log | 6.0 | 198 | 0.7356 | 0.1768 | 0.1741 | 0.1754 | 0.6880 | |
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| No log | 7.0 | 231 | 0.7665 | 0.1699 | 0.1683 | 0.1691 | 0.6841 | |
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| No log | 8.0 | 264 | 0.7958 | 0.1540 | 0.1683 | 0.1608 | 0.6537 | |
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| No log | 9.0 | 297 | 0.8161 | 0.1607 | 0.1567 | 0.1587 | 0.6742 | |
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| No log | 10.0 | 330 | 0.8132 | 0.1776 | 0.1721 | 0.1749 | 0.6778 | |
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| No log | 11.0 | 363 | 0.8387 | 0.1617 | 0.1663 | 0.1640 | 0.6672 | |
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| No log | 12.0 | 396 | 0.8290 | 0.1770 | 0.1760 | 0.1765 | 0.6795 | |
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| No log | 13.0 | 429 | 0.8456 | 0.1770 | 0.1760 | 0.1765 | 0.6750 | |
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| No log | 14.0 | 462 | 0.8377 | 0.1692 | 0.1702 | 0.1697 | 0.6762 | |
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| No log | 15.0 | 495 | 0.8366 | 0.1689 | 0.1683 | 0.1686 | 0.6766 | |
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### Framework versions |
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- Transformers 4.44.0 |
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- Pytorch 2.4.0 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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