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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_1_binary |
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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_1_binary |
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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: 1.1222 |
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- F1: 0.7596 |
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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 | 0.4130 | 0.7517 | |
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| 0.3938 | 2.0 | 576 | 0.4260 | 0.7330 | |
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| 0.3938 | 3.0 | 864 | 0.5000 | 0.7488 | |
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| 0.19 | 4.0 | 1152 | 0.7415 | 0.7487 | |
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| 0.19 | 5.0 | 1440 | 0.8994 | 0.7397 | |
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| 0.0903 | 6.0 | 1728 | 0.9835 | 0.7386 | |
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| 0.0392 | 7.0 | 2016 | 1.1222 | 0.7596 | |
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| 0.0392 | 8.0 | 2304 | 1.2018 | 0.7314 | |
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| 0.0234 | 9.0 | 2592 | 1.2691 | 0.7330 | |
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| 0.0234 | 10.0 | 2880 | 1.2972 | 0.7496 | |
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| 0.0182 | 11.0 | 3168 | 1.4606 | 0.7492 | |
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| 0.0182 | 12.0 | 3456 | 1.4766 | 0.7361 | |
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| 0.006 | 13.0 | 3744 | 1.4888 | 0.7500 | |
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| 0.0057 | 14.0 | 4032 | 1.5684 | 0.7298 | |
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| 0.0057 | 15.0 | 4320 | 1.5354 | 0.7509 | |
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| 0.0058 | 16.0 | 4608 | 1.7733 | 0.7436 | |
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| 0.0058 | 17.0 | 4896 | 1.5695 | 0.7512 | |
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| 0.0089 | 18.0 | 5184 | 1.6593 | 0.7430 | |
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| 0.0089 | 19.0 | 5472 | 1.7092 | 0.7444 | |
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| 0.0048 | 20.0 | 5760 | 1.7206 | 0.7374 | |
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| 0.002 | 21.0 | 6048 | 1.7440 | 0.7343 | |
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| 0.002 | 22.0 | 6336 | 1.7582 | 0.7347 | |
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| 0.0006 | 23.0 | 6624 | 1.7294 | 0.7472 | |
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| 0.0006 | 24.0 | 6912 | 1.7454 | 0.7365 | |
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| 0.0001 | 25.0 | 7200 | 1.7395 | 0.7429 | |
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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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