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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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- sibyl |
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datasets: |
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- dbpedia_14 |
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metrics: |
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- accuracy |
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model-index: |
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- name: bert-base-uncased-dbpedia_14 |
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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: dbpedia_14 |
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type: dbpedia_14 |
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args: dbpedia_14 |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.9902857142857143 |
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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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# bert-base-uncased-dbpedia_14 |
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the dbpedia_14 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0547 |
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- Accuracy: 0.9903 |
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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: 5e-05 |
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- train_batch_size: 8 |
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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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- lr_scheduler_warmup_steps: 34650 |
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- training_steps: 346500 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:| |
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| 1.7757 | 0.03 | 2000 | 0.2732 | 0.9880 | |
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| 0.1002 | 0.06 | 4000 | 0.0620 | 0.9891 | |
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| 0.0547 | 0.09 | 6000 | 0.0723 | 0.9879 | |
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| 0.0558 | 0.12 | 8000 | 0.0678 | 0.9875 | |
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| 0.0534 | 0.14 | 10000 | 0.0554 | 0.9896 | |
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| 0.0632 | 0.17 | 12000 | 0.0670 | 0.9888 | |
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| 0.0612 | 0.2 | 14000 | 0.0733 | 0.9873 | |
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| 0.0667 | 0.23 | 16000 | 0.0623 | 0.9896 | |
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| 0.0636 | 0.26 | 18000 | 0.0836 | 0.9868 | |
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| 0.0705 | 0.29 | 20000 | 0.0776 | 0.9855 | |
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| 0.0726 | 0.32 | 22000 | 0.0805 | 0.9861 | |
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| 0.0778 | 0.35 | 24000 | 0.0713 | 0.9870 | |
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| 0.0713 | 0.38 | 26000 | 0.1277 | 0.9805 | |
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| 0.0965 | 0.4 | 28000 | 0.0810 | 0.9855 | |
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| 0.0881 | 0.43 | 30000 | 0.0910 | 0.985 | |
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### Framework versions |
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- Transformers 4.10.2 |
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- Pytorch 1.7.1 |
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- Datasets 1.6.1 |
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- Tokenizers 0.10.3 |
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