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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: 1.5992 |
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- F1: 0.7687 |
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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 | 0.3960 | 0.7467 | |
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| 0.3988 | 2.0 | 576 | 0.3947 | 0.7487 | |
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| 0.3988 | 3.0 | 864 | 0.4511 | 0.7662 | |
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| 0.1853 | 4.0 | 1152 | 0.7226 | 0.7285 | |
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| 0.1853 | 5.0 | 1440 | 0.9398 | 0.7334 | |
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| 0.0827 | 6.0 | 1728 | 1.0547 | 0.7427 | |
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| 0.0287 | 7.0 | 2016 | 1.1602 | 0.7563 | |
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| 0.0287 | 8.0 | 2304 | 1.3332 | 0.7171 | |
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| 0.0219 | 9.0 | 2592 | 1.3429 | 0.7420 | |
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| 0.0219 | 10.0 | 2880 | 1.2603 | 0.7648 | |
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| 0.0139 | 11.0 | 3168 | 1.4126 | 0.7569 | |
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| 0.0139 | 12.0 | 3456 | 1.3195 | 0.7483 | |
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| 0.0115 | 13.0 | 3744 | 1.4356 | 0.7491 | |
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| 0.0035 | 14.0 | 4032 | 1.5693 | 0.7636 | |
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| 0.0035 | 15.0 | 4320 | 1.4071 | 0.7662 | |
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| 0.0071 | 16.0 | 4608 | 1.4561 | 0.7579 | |
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| 0.0071 | 17.0 | 4896 | 1.5405 | 0.7634 | |
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| 0.0041 | 18.0 | 5184 | 1.5862 | 0.7589 | |
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| 0.0041 | 19.0 | 5472 | 1.6782 | 0.76 | |
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| 0.0024 | 20.0 | 5760 | 1.5699 | 0.7677 | |
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| 0.0006 | 21.0 | 6048 | 1.5991 | 0.7467 | |
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| 0.0006 | 22.0 | 6336 | 1.6205 | 0.7682 | |
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| 0.0003 | 23.0 | 6624 | 1.6334 | 0.7643 | |
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| 0.0003 | 24.0 | 6912 | 1.5992 | 0.7687 | |
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| 0.0011 | 25.0 | 7200 | 1.6053 | 0.7624 | |
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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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