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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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model-index: |
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- name: multi-label-class-classification-on-github-issues |
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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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# multi-label-class-classification-on-github-issues |
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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: 0.1391 |
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- Micro f1: 0.5005 |
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- Macro f1: 0.0340 |
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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: 3e-05 |
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- train_batch_size: 128 |
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- eval_batch_size: 8 |
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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: 15 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Micro f1 | Macro f1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:| |
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| No log | 1.0 | 13 | 0.3988 | 0.3783 | 0.0172 | |
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| No log | 2.0 | 26 | 0.3288 | 0.3791 | 0.0172 | |
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| No log | 3.0 | 39 | 0.2753 | 0.3791 | 0.0172 | |
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| No log | 4.0 | 52 | 0.2347 | 0.3791 | 0.0172 | |
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| No log | 5.0 | 65 | 0.2051 | 0.3791 | 0.0172 | |
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| No log | 6.0 | 78 | 0.1849 | 0.3791 | 0.0172 | |
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| No log | 7.0 | 91 | 0.1710 | 0.3791 | 0.0172 | |
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| No log | 8.0 | 104 | 0.1614 | 0.3791 | 0.0172 | |
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| No log | 9.0 | 117 | 0.1546 | 0.3791 | 0.0172 | |
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| No log | 10.0 | 130 | 0.1497 | 0.3796 | 0.0173 | |
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| No log | 11.0 | 143 | 0.1458 | 0.4143 | 0.0238 | |
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| No log | 12.0 | 156 | 0.1427 | 0.4567 | 0.0295 | |
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| No log | 13.0 | 169 | 0.1406 | 0.4709 | 0.0310 | |
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| No log | 14.0 | 182 | 0.1391 | 0.4886 | 0.0327 | |
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| No log | 15.0 | 195 | 0.1386 | 0.4909 | 0.0330 | |
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### Framework versions |
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- Transformers 4.25.1 |
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- Pytorch 1.13.0+cu116 |
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- Datasets 2.8.0 |
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- Tokenizers 0.13.2 |
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