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--- |
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base_model: |
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- FacebookAI/xlm-roberta-large |
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datasets: |
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- google/xtreme |
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language: |
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- en |
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library_name: transformers |
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license: mit |
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metrics: |
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- f1 |
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- accuracy |
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- precision |
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- recall |
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pipeline_tag: token-classification |
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model-index: |
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- name: xlm-roberta-large-panx-en |
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results: |
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- task: |
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type: token-classification |
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name: Token Classification |
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dataset: |
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name: google/xtreme |
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type: google/xtreme |
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config: PAN-X.en |
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split: validation |
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metrics: |
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- type: precision |
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value: 0.834659287443791 |
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name: Precision |
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- type: recall |
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value: 0.852891276685989 |
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name: Recall |
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- type: f1 |
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value: 0.8436767945176742 |
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name: F1 |
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- type: accuracy |
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value: 0.9357306049468561 |
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name: Accuracy |
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--- |
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# XLM-RoBERTa-Large-PANX-WikiAnn-en |
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This model is a fine-tuned version of [FacebookAI/xlm-roberta-large](https://huggingface.co/FacebookAI/xlm-roberta-large) on the [google/xtreme](https://huggingface.co/datasets/google/xtreme) dataset (English split of the PAN-X). |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2569 |
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- Precision: 0.8347 |
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- Recall: 0.8529 |
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- F1: 0.8437 |
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- Accuracy: 0.9357 |
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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: 4 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 32 |
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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: 5.0 |
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- mixed_precision_training: Native AMP |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 3.0.1 |
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- Tokenizers 0.19.1 |
