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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_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_1_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: 1.7296 |
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- F1: 0.8038 |
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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 | 0.4152 | 0.7903 | |
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| 0.3956 | 2.0 | 576 | 0.4037 | 0.8083 | |
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| 0.3956 | 3.0 | 864 | 0.5601 | 0.7996 | |
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| 0.181 | 4.0 | 1152 | 0.8571 | 0.8023 | |
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| 0.181 | 5.0 | 1440 | 0.9704 | 0.7822 | |
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| 0.0935 | 6.0 | 1728 | 0.9509 | 0.8074 | |
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| 0.0418 | 7.0 | 2016 | 1.1813 | 0.7736 | |
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| 0.0418 | 8.0 | 2304 | 1.2619 | 0.7859 | |
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| 0.0134 | 9.0 | 2592 | 1.4275 | 0.7863 | |
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| 0.0134 | 10.0 | 2880 | 1.4035 | 0.8019 | |
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| 0.0127 | 11.0 | 3168 | 1.4903 | 0.7897 | |
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| 0.0127 | 12.0 | 3456 | 1.5853 | 0.7919 | |
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| 0.0061 | 13.0 | 3744 | 1.6628 | 0.7957 | |
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| 0.0058 | 14.0 | 4032 | 1.5736 | 0.8060 | |
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| 0.0058 | 15.0 | 4320 | 1.6226 | 0.7929 | |
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| 0.0065 | 16.0 | 4608 | 1.6395 | 0.8010 | |
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| 0.0065 | 17.0 | 4896 | 1.6556 | 0.7993 | |
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| 0.002 | 18.0 | 5184 | 1.7075 | 0.8030 | |
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| 0.002 | 19.0 | 5472 | 1.6925 | 0.7964 | |
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| 0.0058 | 20.0 | 5760 | 1.6511 | 0.8030 | |
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| 0.0013 | 21.0 | 6048 | 1.6135 | 0.8037 | |
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| 0.0013 | 22.0 | 6336 | 1.6739 | 0.8028 | |
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| 0.0001 | 23.0 | 6624 | 1.7014 | 0.8109 | |
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| 0.0001 | 24.0 | 6912 | 1.7015 | 0.8045 | |
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| 0.002 | 25.0 | 7200 | 1.7296 | 0.8038 | |
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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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