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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_6_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_6_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: 1.7209 |
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- F1: 0.8156 |
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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 | 290 | 0.4115 | 0.8048 | |
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| 0.3976 | 2.0 | 580 | 0.3980 | 0.8156 | |
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| 0.3976 | 3.0 | 870 | 0.5953 | 0.8142 | |
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| 0.1965 | 4.0 | 1160 | 0.7940 | 0.8057 | |
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| 0.1965 | 5.0 | 1450 | 0.8098 | 0.8069 | |
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| 0.0847 | 6.0 | 1740 | 1.0293 | 0.7913 | |
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| 0.03 | 7.0 | 2030 | 1.1649 | 0.8073 | |
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| 0.03 | 8.0 | 2320 | 1.2876 | 0.7973 | |
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| 0.0166 | 9.0 | 2610 | 1.3260 | 0.8038 | |
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| 0.0166 | 10.0 | 2900 | 1.3523 | 0.8084 | |
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| 0.0062 | 11.0 | 3190 | 1.3814 | 0.8097 | |
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| 0.0062 | 12.0 | 3480 | 1.4134 | 0.8165 | |
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| 0.0113 | 13.0 | 3770 | 1.5374 | 0.8068 | |
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| 0.006 | 14.0 | 4060 | 1.5808 | 0.8100 | |
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| 0.006 | 15.0 | 4350 | 1.6551 | 0.7972 | |
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| 0.0088 | 16.0 | 4640 | 1.5793 | 0.8116 | |
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| 0.0088 | 17.0 | 4930 | 1.6134 | 0.8143 | |
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| 0.0021 | 18.0 | 5220 | 1.6204 | 0.8119 | |
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| 0.0031 | 19.0 | 5510 | 1.7006 | 0.8029 | |
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| 0.0031 | 20.0 | 5800 | 1.6777 | 0.8145 | |
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| 0.0019 | 21.0 | 6090 | 1.7202 | 0.8079 | |
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| 0.0019 | 22.0 | 6380 | 1.7539 | 0.8053 | |
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| 0.0008 | 23.0 | 6670 | 1.7408 | 0.8119 | |
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| 0.0008 | 24.0 | 6960 | 1.7388 | 0.8176 | |
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| 0.0014 | 25.0 | 7250 | 1.7209 | 0.8156 | |
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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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