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--- |
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license: mit |
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tags: |
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- generated_from_trainer |
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metrics: |
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- f1 |
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model-index: |
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- name: edos-2023-baseline-xlm-roberta-base-label_vector |
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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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# edos-2023-baseline-xlm-roberta-base-label_vector |
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This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.5797 |
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- F1: 0.2746 |
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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: 1e-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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- lr_scheduler_warmup_steps: 5 |
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- num_epochs: 12 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:------:| |
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| 2.1596 | 1.18 | 100 | 1.9772 | 0.0891 | |
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| 1.8651 | 2.35 | 200 | 1.7720 | 0.1159 | |
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| 1.6848 | 3.53 | 300 | 1.7193 | 0.1892 | |
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| 1.5532 | 4.71 | 400 | 1.6794 | 0.2191 | |
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| 1.466 | 5.88 | 500 | 1.6095 | 0.2419 | |
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| 1.3562 | 7.06 | 600 | 1.5771 | 0.2694 | |
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| 1.2909 | 8.24 | 700 | 1.5761 | 0.2707 | |
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| 1.2027 | 9.41 | 800 | 1.5747 | 0.2764 | |
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| 1.192 | 10.59 | 900 | 1.5893 | 0.2686 | |
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| 1.1256 | 11.76 | 1000 | 1.5797 | 0.2746 | |
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### Framework versions |
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- Transformers 4.24.0 |
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- Pytorch 1.12.1+cu113 |
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- Datasets 2.7.1 |
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- Tokenizers 0.13.2 |
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