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--- |
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tags: |
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- generated_from_trainer |
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metrics: |
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- precision |
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- recall |
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- f1 |
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- accuracy |
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model-index: |
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- name: 8Agos |
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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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# roberta_finetuned_astronomicalNER |
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This model is a fine-tuned version of [xlm-roberta-large-finetuned-conll03-english](https://huggingface.co/xlm-roberta-large-finetuned-conll03-english) for NER on astronomical objects. |
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The dataset comes from the Shared Task [DEAL: Detecting Entities in the Astrophysics Literature](https://ui.adsabs.harvard.edu/WIESP/2022/SharedTasks) |
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The model achieves the following results on the evaluation set: |
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- Loss: 0.1416 |
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- Precision: 0.7659 |
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- Recall: 0.7986 |
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- F1: 0.7819 |
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- Accuracy: 0.9640 |
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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: 8 |
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- eval_batch_size: 8 |
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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: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
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| No log | 1.0 | 176 | 0.1571 | 0.7362 | 0.7788 | 0.7569 | 0.9593 | |
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| No log | 2.0 | 352 | 0.1416 | 0.7529 | 0.7831 | 0.7677 | 0.9624 | |
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| 0.1109 | 3.0 | 528 | 0.1416 | 0.7659 | 0.7986 | 0.7819 | 0.9640 | |
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### Framework versions |
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- Transformers 4.21.1 |
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- Pytorch 1.12.0+cu113 |
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- Datasets 2.4.0 |
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- Tokenizers 0.12.1 |
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