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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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- accuracy |
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model-index: |
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- name: bert-finetuned-sla |
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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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# bert-finetuned-sla |
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2965 |
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- F1: 0.7121 |
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- Roc Auc: 0.8162 |
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- Accuracy: 0.5098 |
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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: 4 |
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- eval_batch_size: 4 |
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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: 20 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:| |
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| No log | 1.0 | 30 | 0.5013 | 0.1842 | 0.5497 | 0.0784 | |
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| No log | 2.0 | 60 | 0.4369 | 0.15 | 0.5337 | 0.0784 | |
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| No log | 3.0 | 90 | 0.3724 | 0.5794 | 0.7141 | 0.4118 | |
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| No log | 4.0 | 120 | 0.3463 | 0.6560 | 0.7738 | 0.4314 | |
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| No log | 5.0 | 150 | 0.3212 | 0.6452 | 0.7664 | 0.4314 | |
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| No log | 6.0 | 180 | 0.3092 | 0.6190 | 0.7539 | 0.4510 | |
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| No log | 7.0 | 210 | 0.3096 | 0.6772 | 0.7885 | 0.4902 | |
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| No log | 8.0 | 240 | 0.3025 | 0.6870 | 0.7997 | 0.4706 | |
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| No log | 9.0 | 270 | 0.3118 | 0.6875 | 0.7958 | 0.4902 | |
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| No log | 10.0 | 300 | 0.2965 | 0.7121 | 0.8162 | 0.5098 | |
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| No log | 11.0 | 330 | 0.2971 | 0.7023 | 0.8088 | 0.4902 | |
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| No log | 12.0 | 360 | 0.3071 | 0.6866 | 0.8036 | 0.4510 | |
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| No log | 13.0 | 390 | 0.3015 | 0.6718 | 0.7907 | 0.4510 | |
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| No log | 14.0 | 420 | 0.3087 | 0.6718 | 0.7907 | 0.4314 | |
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| No log | 15.0 | 450 | 0.2978 | 0.6970 | 0.8071 | 0.4706 | |
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| No log | 16.0 | 480 | 0.3058 | 0.6718 | 0.7907 | 0.4510 | |
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| 0.219 | 17.0 | 510 | 0.3039 | 0.6769 | 0.7924 | 0.4510 | |
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| 0.219 | 18.0 | 540 | 0.3015 | 0.6870 | 0.7997 | 0.4706 | |
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| 0.219 | 19.0 | 570 | 0.3011 | 0.6870 | 0.7997 | 0.4706 | |
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| 0.219 | 20.0 | 600 | 0.3014 | 0.6870 | 0.7997 | 0.4706 | |
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### Framework versions |
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- Transformers 4.26.0 |
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- Pytorch 1.13.1+cu116 |
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- Datasets 2.9.0 |
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- Tokenizers 0.13.2 |
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