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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: 0.3274 |
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- F1: 0.6555 |
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- Roc Auc: 0.7660 |
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- Accuracy: 0.5294 |
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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 | 0.4994 | 0.0 | 0.5 | 0.0 | |
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| No log | 2.0 | 60 | 0.4408 | 0.0 | 0.5 | 0.0 | |
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| No log | 3.0 | 90 | 0.3761 | 0.4444 | 0.6462 | 0.1961 | |
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| No log | 4.0 | 120 | 0.3438 | 0.6496 | 0.7604 | 0.4706 | |
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| No log | 5.0 | 150 | 0.3274 | 0.6555 | 0.7660 | 0.5294 | |
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| No log | 6.0 | 180 | 0.3093 | 0.6557 | 0.7699 | 0.4706 | |
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| No log | 7.0 | 210 | 0.3083 | 0.6560 | 0.7738 | 0.5098 | |
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| No log | 8.0 | 240 | 0.3030 | 0.6457 | 0.7703 | 0.4706 | |
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| No log | 9.0 | 270 | 0.3096 | 0.6667 | 0.7811 | 0.4902 | |
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| No log | 10.0 | 300 | 0.2976 | 0.6718 | 0.7907 | 0.5098 | |
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| No log | 11.0 | 330 | 0.2986 | 0.6769 | 0.7924 | 0.5294 | |
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| No log | 12.0 | 360 | 0.3046 | 0.6562 | 0.7777 | 0.5098 | |
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| No log | 13.0 | 390 | 0.2988 | 0.6870 | 0.7997 | 0.4902 | |
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| No log | 14.0 | 420 | 0.3026 | 0.6769 | 0.7924 | 0.5098 | |
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| No log | 15.0 | 450 | 0.3005 | 0.6870 | 0.7997 | 0.5098 | |
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| No log | 16.0 | 480 | 0.3012 | 0.6822 | 0.7941 | 0.5098 | |
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| 0.2216 | 17.0 | 510 | 0.3013 | 0.6977 | 0.8032 | 0.5294 | |
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| 0.2216 | 18.0 | 540 | 0.3033 | 0.6977 | 0.8032 | 0.5294 | |
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| 0.2216 | 19.0 | 570 | 0.3024 | 0.6977 | 0.8032 | 0.5294 | |
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| 0.2216 | 20.0 | 600 | 0.3027 | 0.6923 | 0.8015 | 0.5098 | |
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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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