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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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metrics: |
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- f1 |
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model-index: |
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- name: distilbert-base-uncased_fold_7_binary_v1 |
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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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# distilbert-base-uncased_fold_7_binary_v1 |
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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: 1.8361 |
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- F1: 0.7958 |
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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: 25 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:------:| |
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| No log | 1.0 | 288 | 0.4025 | 0.8071 | |
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| 0.3986 | 2.0 | 576 | 0.3979 | 0.8072 | |
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| 0.3986 | 3.0 | 864 | 0.5170 | 0.8041 | |
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| 0.1761 | 4.0 | 1152 | 0.7946 | 0.7940 | |
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| 0.1761 | 5.0 | 1440 | 1.0000 | 0.7937 | |
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| 0.0705 | 6.0 | 1728 | 1.1484 | 0.7875 | |
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| 0.0294 | 7.0 | 2016 | 1.1548 | 0.8042 | |
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| 0.0294 | 8.0 | 2304 | 1.3036 | 0.8069 | |
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| 0.0171 | 9.0 | 2592 | 1.4043 | 0.7943 | |
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| 0.0171 | 10.0 | 2880 | 1.3356 | 0.8002 | |
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| 0.0154 | 11.0 | 3168 | 1.4528 | 0.7996 | |
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| 0.0154 | 12.0 | 3456 | 1.5514 | 0.7991 | |
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| 0.005 | 13.0 | 3744 | 1.6341 | 0.8046 | |
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| 0.0038 | 14.0 | 4032 | 1.6240 | 0.7984 | |
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| 0.0038 | 15.0 | 4320 | 1.7476 | 0.8014 | |
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| 0.0037 | 16.0 | 4608 | 1.6666 | 0.7982 | |
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| 0.0037 | 17.0 | 4896 | 1.7495 | 0.7950 | |
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| 0.0083 | 18.0 | 5184 | 1.6993 | 0.7932 | |
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| 0.0083 | 19.0 | 5472 | 1.6573 | 0.8077 | |
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| 0.002 | 20.0 | 5760 | 1.7430 | 0.7980 | |
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| 0.0012 | 21.0 | 6048 | 1.8135 | 0.7955 | |
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| 0.0012 | 22.0 | 6336 | 1.8316 | 0.7972 | |
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| 0.0022 | 23.0 | 6624 | 1.8717 | 0.7926 | |
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| 0.0022 | 24.0 | 6912 | 1.8183 | 0.7978 | |
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| 0.0014 | 25.0 | 7200 | 1.8361 | 0.7958 | |
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### Framework versions |
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- Transformers 4.21.0 |
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- Pytorch 1.12.0+cu113 |
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- Datasets 2.4.0 |
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- Tokenizers 0.12.1 |
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