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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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datasets: |
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- health_fact |
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metrics: |
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- accuracy |
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- f1 |
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model-index: |
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- name: distilbert-base-uncased-finetuned-health_facts |
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results: |
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- task: |
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name: Text Classification |
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type: text-classification |
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dataset: |
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name: health_fact |
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type: health_fact |
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args: default |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.628500823723229 |
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- name: F1 |
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type: f1 |
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value: 0.6544946803476833 |
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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-health_facts |
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the health_fact dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.1227 |
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- Accuracy: 0.6285 |
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- F1: 0.6545 |
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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: 64 |
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- eval_batch_size: 64 |
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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: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| |
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| 1.1367 | 1.0 | 154 | 0.9423 | 0.5560 | 0.6060 | |
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| 0.9444 | 2.0 | 308 | 0.9267 | 0.5733 | 0.6170 | |
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| 0.8248 | 3.0 | 462 | 0.9483 | 0.5832 | 0.6256 | |
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| 0.7213 | 4.0 | 616 | 1.0119 | 0.5815 | 0.6219 | |
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| 0.608 | 5.0 | 770 | 1.1227 | 0.6285 | 0.6545 | |
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### Framework versions |
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- Transformers 4.11.3 |
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- Pytorch 1.10.0 |
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- Datasets 1.16.1 |
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- Tokenizers 0.10.3 |
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