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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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- accuracy |
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- f1 |
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base_model: bert-base-uncased |
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model-index: |
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- name: bert-base-uncased-ft-news |
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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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# bert-base-uncased-ft-news |
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the [news](https://huggingface.co/datasets/steciuk/news) dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4300 |
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- Accuracy: 0.9 |
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- F1: 0.8783 |
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and flowing results on the testing set: |
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- Accuracy: 0.8954 |
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- F1: 0.8784 |
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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: 3 |
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- mixed_precision_training: Native AMP |
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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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| 0.4196 | 0.37 | 120 | 0.3051 | 0.8875 | 0.8566 | |
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| 0.3101 | 0.75 | 240 | 0.2979 | 0.8953 | 0.8743 | |
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| 0.2693 | 1.12 | 360 | 0.3162 | 0.9016 | 0.8831 | |
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| 0.2078 | 1.5 | 480 | 0.3298 | 0.8984 | 0.8767 | |
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| 0.1725 | 1.87 | 600 | 0.3801 | 0.9047 | 0.8851 | |
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| 0.1369 | 2.24 | 720 | 0.3901 | 0.8938 | 0.8677 | |
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| 0.1101 | 2.62 | 840 | 0.4160 | 0.9016 | 0.8805 | |
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| 0.1019 | 2.99 | 960 | 0.4300 | 0.9 | 0.8783 | |
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### Framework versions |
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- Transformers 4.25.1 |
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- Pytorch 1.13.0+cu116 |
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- Datasets 2.8.0 |
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- Tokenizers 0.13.2 |
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