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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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base_model: bert-base-uncased |
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model-index: |
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- name: mitre-bert-base-uncased |
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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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# mitre-bert-base-uncased |
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.1257 |
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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: 32 |
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- eval_batch_size: 32 |
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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: 100 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:-----:|:---------------:| |
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| 2.0301 | 2.72 | 1000 | 1.6360 | |
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| 1.4454 | 5.45 | 2000 | 1.4483 | |
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| 1.2259 | 8.17 | 3000 | 1.3658 | |
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| 1.0811 | 10.9 | 4000 | 1.2872 | |
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| 0.9744 | 13.62 | 5000 | 1.2763 | |
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| 0.8601 | 16.35 | 6000 | 1.2343 | |
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| 0.7918 | 19.07 | 7000 | 1.1792 | |
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| 0.7375 | 21.8 | 8000 | 1.1792 | |
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| 0.6806 | 24.52 | 9000 | 1.1332 | |
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| 0.6274 | 27.25 | 10000 | 1.1129 | |
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| 0.5803 | 29.97 | 11000 | 1.1239 | |
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| 0.5403 | 32.7 | 12000 | 1.1224 | |
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| 0.5028 | 35.42 | 13000 | 1.1344 | |
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| 0.4661 | 38.15 | 14000 | 1.1215 | |
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| 0.4463 | 40.87 | 15000 | 1.1453 | |
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| 0.4102 | 43.6 | 16000 | 1.0828 | |
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| 0.3866 | 46.32 | 17000 | 1.1044 | |
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| 0.3749 | 49.05 | 18000 | 1.1199 | |
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| 0.3554 | 51.77 | 19000 | 1.0722 | |
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| 0.3288 | 54.5 | 20000 | 1.1167 | |
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| 0.319 | 57.22 | 21000 | 1.1110 | |
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| 0.3064 | 59.95 | 22000 | 1.0821 | |
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| 0.2938 | 62.67 | 23000 | 1.0702 | |
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| 0.2741 | 65.4 | 24000 | 1.0373 | |
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| 0.2626 | 68.12 | 25000 | 1.1236 | |
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| 0.2525 | 70.84 | 26000 | 1.0831 | |
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| 0.2433 | 73.57 | 27000 | 1.0691 | |
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| 0.2376 | 76.29 | 28000 | 1.0647 | |
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| 0.2303 | 79.02 | 29000 | 1.0851 | |
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| 0.2164 | 81.74 | 30000 | 1.0864 | |
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| 0.2103 | 84.47 | 31000 | 1.0502 | |
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| 0.2049 | 87.19 | 32000 | 1.0644 | |
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| 0.2011 | 89.92 | 33000 | 1.0262 | |
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| 0.2024 | 92.64 | 34000 | 1.0738 | |
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| 0.1889 | 95.37 | 35000 | 1.0640 | |
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| 0.1846 | 98.09 | 36000 | 1.1257 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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