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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_4_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_4_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: 1.5144 |
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- F1: 0.8245 |
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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 | 289 | 0.3756 | 0.8175 | |
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| 0.3977 | 2.0 | 578 | 0.3672 | 0.8336 | |
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| 0.3977 | 3.0 | 867 | 0.4997 | 0.8276 | |
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| 0.1972 | 4.0 | 1156 | 0.6597 | 0.8244 | |
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| 0.1972 | 5.0 | 1445 | 0.8501 | 0.8195 | |
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| 0.0824 | 6.0 | 1734 | 1.0074 | 0.8097 | |
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| 0.037 | 7.0 | 2023 | 1.1122 | 0.8131 | |
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| 0.037 | 8.0 | 2312 | 1.0963 | 0.8189 | |
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| 0.0182 | 9.0 | 2601 | 1.2511 | 0.8125 | |
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| 0.0182 | 10.0 | 2890 | 1.2255 | 0.8141 | |
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| 0.0121 | 11.0 | 3179 | 1.3120 | 0.8187 | |
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| 0.0121 | 12.0 | 3468 | 1.4182 | 0.8165 | |
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| 0.0079 | 13.0 | 3757 | 1.4142 | 0.8218 | |
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| 0.0081 | 14.0 | 4046 | 1.4765 | 0.8150 | |
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| 0.0081 | 15.0 | 4335 | 1.3510 | 0.8187 | |
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| 0.0109 | 16.0 | 4624 | 1.3455 | 0.8255 | |
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| 0.0109 | 17.0 | 4913 | 1.4157 | 0.8234 | |
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| 0.0022 | 18.0 | 5202 | 1.4651 | 0.8197 | |
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| 0.0022 | 19.0 | 5491 | 1.4388 | 0.8267 | |
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| 0.0017 | 20.0 | 5780 | 1.4552 | 0.8304 | |
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| 0.0005 | 21.0 | 6069 | 1.5357 | 0.8248 | |
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| 0.0005 | 22.0 | 6358 | 1.4924 | 0.8241 | |
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| 0.0009 | 23.0 | 6647 | 1.4865 | 0.8248 | |
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| 0.0009 | 24.0 | 6936 | 1.4697 | 0.8275 | |
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| 0.0013 | 25.0 | 7225 | 1.5144 | 0.8245 | |
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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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