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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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model-index: |
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- name: distilbert-base-uncased-finetuned-combinedmodel1-ner |
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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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# distilbert-base-uncased-finetuned-combinedmodel1-ner |
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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: 2.3126 |
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- Precision: 0.0289 |
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- Recall: 0.1443 |
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- F1: 0.0481 |
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- Accuracy: 0.7058 |
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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: 3e-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: 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 | 312 | 1.5290 | 0.0431 | 0.2278 | 0.0725 | 0.6990 | |
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| 0.1106 | 2.0 | 624 | 2.0923 | 0.0341 | 0.1722 | 0.0569 | 0.7041 | |
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| 0.1106 | 3.0 | 936 | 2.3126 | 0.0289 | 0.1443 | 0.0481 | 0.7058 | |
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### Framework versions |
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- Transformers 4.17.0 |
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- Pytorch 1.10.0+cu111 |
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- Datasets 1.18.4 |
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- Tokenizers 0.11.6 |
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