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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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- accuracy |
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- precision |
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- recall |
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- f1 |
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model-index: |
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- name: FULL-3epoch-XLMRoBERTa-finetuned-CEFR_ner-60000news |
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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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# FULL-3epoch-XLMRoBERTa-finetuned-CEFR_ner-60000news |
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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: 0.2571 |
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- Accuracy: 0.3011 |
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- Precision: 0.7306 |
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- Recall: 0.6846 |
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- F1: 0.5945 |
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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: 64 |
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- eval_batch_size: 64 |
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- seed: 42 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 512 |
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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: 100 |
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- num_epochs: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
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|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
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| No log | 0.9923 | 97 | 0.5290 | 0.2637 | 0.6408 | 0.5061 | 0.4053 | |
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| No log | 1.9949 | 195 | 0.2969 | 0.2962 | 0.7163 | 0.6474 | 0.5560 | |
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| No log | 2.9770 | 291 | 0.2571 | 0.3011 | 0.7306 | 0.6846 | 0.5945 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.2.1 |
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- Datasets 2.19.2 |
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- Tokenizers 0.19.1 |
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