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--- |
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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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- 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: my_awesome_ner-token_classification_v1.0 |
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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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# my_awesome_ner-token_classification_v1.0 |
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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: 0.8650 |
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- Precision: 0.4582 |
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- Recall: 0.5502 |
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- F1: 0.5 |
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- Accuracy: 0.8053 |
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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: 16 |
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- eval_batch_size: 16 |
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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: cosine |
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- num_epochs: 20 |
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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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| 1.0426 | 1.9912 | 225 | 0.8857 | 0.3633 | 0.3365 | 0.3494 | 0.7753 | |
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| 0.7028 | 3.9823 | 450 | 0.7244 | 0.4994 | 0.4647 | 0.4815 | 0.8136 | |
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| 0.5281 | 5.9735 | 675 | 0.6965 | 0.4933 | 0.5513 | 0.5207 | 0.8124 | |
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| 0.3767 | 7.9646 | 900 | 0.7331 | 0.4760 | 0.5406 | 0.5063 | 0.8169 | |
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| 0.2995 | 9.9558 | 1125 | 0.7731 | 0.4646 | 0.5321 | 0.4960 | 0.8158 | |
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| 0.2731 | 11.9469 | 1350 | 0.8100 | 0.4650 | 0.5395 | 0.4995 | 0.8074 | |
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| 0.2259 | 13.9381 | 1575 | 0.8500 | 0.4769 | 0.5502 | 0.5109 | 0.8112 | |
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| 0.1916 | 15.9292 | 1800 | 0.8650 | 0.4582 | 0.5502 | 0.5 | 0.8053 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.1.2 |
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- Datasets 2.19.2 |
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- Tokenizers 0.19.1 |
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