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--- |
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license: apache-2.0 |
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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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base_model: distilbert-base-uncased |
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model-index: |
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- name: kg_model |
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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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# kg_model |
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3039 |
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- Precision: 0.7629 |
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- Recall: 0.7025 |
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- F1: 0.7315 |
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- Accuracy: 0.8965 |
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## Model description |
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Lite model to extract entities and relation between them, could be leveraged for Question Answering and Querying tasks. |
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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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| 0.3736 | 1.0 | 1063 | 0.3379 | 0.7542 | 0.6217 | 0.6816 | 0.8813 | |
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| 0.3078 | 2.0 | 2126 | 0.3075 | 0.7728 | 0.6678 | 0.7164 | 0.8929 | |
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| 0.267 | 3.0 | 3189 | 0.3017 | 0.7597 | 0.6999 | 0.7285 | 0.8954 | |
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| 0.2455 | 4.0 | 4252 | 0.3039 | 0.7629 | 0.7025 | 0.7315 | 0.8965 | |
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### Framework versions |
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- Transformers 4.27.3 |
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- Pytorch 1.13.1+cu116 |
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- Datasets 2.10.1 |
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- Tokenizers 0.13.2 |
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