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--- |
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license: apache-2.0 |
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base_model: distilbert-base-uncased |
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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: RISE_NER4 |
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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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# RISE_NER4 |
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1028 |
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- Precision: 0.8937 |
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- Recall: 0.9059 |
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- F1: 0.8997 |
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- Accuracy: 0.9834 |
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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: linear |
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- num_epochs: 4 |
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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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| 0.012 | 1.0 | 16410 | 0.0639 | 0.8898 | 0.8978 | 0.8938 | 0.9827 | |
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| 0.0074 | 2.0 | 32820 | 0.0788 | 0.9006 | 0.8950 | 0.8978 | 0.9831 | |
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| 0.003 | 3.0 | 49230 | 0.0930 | 0.8938 | 0.9012 | 0.8975 | 0.9831 | |
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| 0.0014 | 4.0 | 65640 | 0.1028 | 0.8937 | 0.9059 | 0.8997 | 0.9834 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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