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--- |
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license: mit |
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base_model: xlm-roberta-base |
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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: xlm-roberta-base-finetuned-panx-hi-ta |
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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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# xlm-roberta-base-finetuned-panx-hi-ta |
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This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4635 |
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- F1: 0.8674 |
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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: 5e-05 |
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- train_batch_size: 24 |
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- eval_batch_size: 24 |
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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 | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:------:| |
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| 0.4856 | 1.0 | 372 | 0.2799 | 0.7713 | |
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| 0.2483 | 2.0 | 744 | 0.2545 | 0.8067 | |
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| 0.1844 | 3.0 | 1116 | 0.2355 | 0.8147 | |
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| 0.1486 | 4.0 | 1488 | 0.2546 | 0.8136 | |
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| 0.1373 | 5.0 | 1860 | 0.2560 | 0.8167 | |
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| 0.0839 | 6.0 | 2232 | 0.2699 | 0.8232 | |
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| 0.0658 | 7.0 | 2604 | 0.3030 | 0.8209 | |
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| 0.05 | 8.0 | 2976 | 0.3625 | 0.8458 | |
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| 0.0382 | 9.0 | 3348 | 0.3777 | 0.8445 | |
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| 0.031 | 10.0 | 3720 | 0.3732 | 0.8514 | |
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| 0.0246 | 11.0 | 4092 | 0.3994 | 0.8579 | |
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| 0.0144 | 12.0 | 4464 | 0.4308 | 0.8507 | |
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| 0.0137 | 13.0 | 4836 | 0.4203 | 0.8499 | |
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| 0.0085 | 14.0 | 5208 | 0.4428 | 0.8613 | |
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| 0.0067 | 15.0 | 5580 | 0.4589 | 0.8563 | |
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| 0.0062 | 16.0 | 5952 | 0.4375 | 0.8609 | |
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| 0.0047 | 17.0 | 6324 | 0.4448 | 0.8610 | |
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| 0.0026 | 18.0 | 6696 | 0.4540 | 0.8624 | |
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| 0.0017 | 19.0 | 7068 | 0.4645 | 0.8658 | |
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| 0.0021 | 20.0 | 7440 | 0.4635 | 0.8674 | |
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### Framework versions |
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- Transformers 4.33.1 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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