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--- |
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library_name: transformers |
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license: mit |
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base_model: FacebookAI/xlm-roberta-base |
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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: metadata-cls-no-gov-8k-vnnic-xml |
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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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# metadata-cls-no-gov-8k-vnnic-xml |
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This model is a fine-tuned version of [FacebookAI/xlm-roberta-base](https://huggingface.co./FacebookAI/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: 0.3308 |
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- Accuracy: 0.9345 |
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- F1: 0.7072 |
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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: 10 |
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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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| No log | 0.5703 | 150 | 0.2151 | 0.9411 | 0.4945 | |
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| 0.5567 | 1.1407 | 300 | 0.2789 | 0.9121 | 0.4579 | |
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| 0.5567 | 1.7110 | 450 | 0.2676 | 0.9130 | 0.6930 | |
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| 0.2703 | 2.2814 | 600 | 0.1926 | 0.9345 | 0.7071 | |
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| 0.2703 | 2.8517 | 750 | 0.1984 | 0.9411 | 0.7390 | |
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| 0.2055 | 3.4221 | 900 | 0.2503 | 0.9205 | 0.6689 | |
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| 0.1573 | 3.9924 | 1050 | 0.1895 | 0.9476 | 0.7332 | |
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| 0.1573 | 4.5627 | 1200 | 0.3001 | 0.9130 | 0.6974 | |
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| 0.1287 | 5.1331 | 1350 | 0.1834 | 0.9495 | 0.7302 | |
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| 0.1287 | 5.7034 | 1500 | 0.2586 | 0.9429 | 0.7345 | |
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| 0.1022 | 6.2738 | 1650 | 0.3486 | 0.9261 | 0.7055 | |
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| 0.1022 | 6.8441 | 1800 | 0.3064 | 0.9317 | 0.7053 | |
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| 0.085 | 7.4144 | 1950 | 0.3445 | 0.9308 | 0.7086 | |
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| 0.0689 | 7.9848 | 2100 | 0.3342 | 0.9336 | 0.7130 | |
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| 0.0689 | 8.5551 | 2250 | 0.3272 | 0.9345 | 0.7074 | |
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| 0.0525 | 9.1255 | 2400 | 0.3391 | 0.9345 | 0.7030 | |
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| 0.0525 | 9.6958 | 2550 | 0.3308 | 0.9345 | 0.7072 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.1.2 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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