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--- |
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license: apache-2.0 |
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base_model: distilbert-base-uncased |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: finetuned-DSCS24-mitre-distilbert-base-uncased-fill-mask |
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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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# finetuned-DSCS24-mitre-distilbert-base-uncased-fill-mask |
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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: 1.9549 |
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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: 1e-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: cosine |
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- num_epochs: 20 |
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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 | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 2.6456 | 1.0 | 65 | 2.3685 | |
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| 2.3833 | 2.0 | 130 | 2.2661 | |
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| 2.282 | 3.0 | 195 | 2.2728 | |
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| 2.1715 | 4.0 | 260 | 2.1675 | |
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| 2.1186 | 5.0 | 325 | 2.1354 | |
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| 2.0968 | 6.0 | 390 | 2.0318 | |
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| 2.0885 | 7.0 | 455 | 2.1233 | |
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| 2.0212 | 8.0 | 520 | 2.0152 | |
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| 1.9305 | 9.0 | 585 | 2.0134 | |
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| 1.9843 | 10.0 | 650 | 2.0334 | |
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| 1.9682 | 11.0 | 715 | 1.9611 | |
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| 1.9383 | 12.0 | 780 | 2.0051 | |
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| 1.9075 | 13.0 | 845 | 1.9790 | |
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| 1.9107 | 14.0 | 910 | 1.9532 | |
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| 1.9352 | 15.0 | 975 | 1.9677 | |
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| 1.9102 | 16.0 | 1040 | 1.9569 | |
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| 1.9065 | 17.0 | 1105 | 1.9143 | |
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| 1.8659 | 18.0 | 1170 | 1.9818 | |
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| 1.8807 | 19.0 | 1235 | 1.9321 | |
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| 1.9088 | 20.0 | 1300 | 1.9549 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.2 |
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- Tokenizers 0.19.1 |
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