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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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datasets: |
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- filter_v2 |
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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: favs_filter_classification_v2 |
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results: |
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- task: |
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name: Text Classification |
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type: text-classification |
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dataset: |
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name: filter_v2 |
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type: filter_v2 |
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config: default |
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split: train |
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args: default |
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metrics: |
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- name: F1 |
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type: f1 |
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value: 0.9761904761904762 |
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- name: Accuracy |
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type: accuracy |
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value: 0.9545454545454546 |
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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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# favs_filter_classification_v2 |
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This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the filter_v2 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2016 |
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- F1: 0.9762 |
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- Roc Auc: 0.9844 |
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- Accuracy: 0.9545 |
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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: 1.5e-05 |
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- train_batch_size: 8 |
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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: 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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| 0.6596 | 1.0 | 16 | 0.6086 | 0.2687 | 0.5474 | 0.0 | |
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| 0.5448 | 2.0 | 32 | 0.5354 | 0.3824 | 0.6063 | 0.0 | |
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| 0.5106 | 3.0 | 48 | 0.4874 | 0.4444 | 0.6382 | 0.0455 | |
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| 0.4353 | 4.0 | 64 | 0.4301 | 0.5352 | 0.6889 | 0.1818 | |
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| 0.3699 | 5.0 | 80 | 0.3890 | 0.6579 | 0.7640 | 0.3636 | |
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| 0.349 | 6.0 | 96 | 0.3663 | 0.6667 | 0.7633 | 0.3182 | |
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| 0.3104 | 7.0 | 112 | 0.3327 | 0.7105 | 0.7953 | 0.4545 | |
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| 0.3023 | 8.0 | 128 | 0.2971 | 0.7733 | 0.8303 | 0.5455 | |
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| 0.2676 | 9.0 | 144 | 0.2766 | 0.8395 | 0.8861 | 0.7727 | |
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| 0.2374 | 10.0 | 160 | 0.2541 | 0.8537 | 0.8980 | 0.7727 | |
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| 0.2238 | 11.0 | 176 | 0.2399 | 0.9024 | 0.9293 | 0.8182 | |
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| 0.2084 | 12.0 | 192 | 0.2221 | 0.9286 | 0.9531 | 0.8636 | |
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| 0.2143 | 13.0 | 208 | 0.2138 | 0.9286 | 0.9531 | 0.8636 | |
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| 0.1846 | 14.0 | 224 | 0.2016 | 0.9762 | 0.9844 | 0.9545 | |
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| 0.1812 | 15.0 | 240 | 0.1957 | 0.9762 | 0.9844 | 0.9545 | |
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| 0.1756 | 16.0 | 256 | 0.1881 | 0.9647 | 0.9806 | 0.9091 | |
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| 0.1662 | 17.0 | 272 | 0.1845 | 0.9762 | 0.9844 | 0.9545 | |
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| 0.1715 | 18.0 | 288 | 0.1802 | 0.9762 | 0.9844 | 0.9545 | |
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| 0.1585 | 19.0 | 304 | 0.1782 | 0.9762 | 0.9844 | 0.9545 | |
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| 0.1595 | 20.0 | 320 | 0.1775 | 0.9762 | 0.9844 | 0.9545 | |
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### Framework versions |
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- Transformers 4.21.1 |
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- Pytorch 1.12.1 |
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- Datasets 2.4.0 |
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- Tokenizers 0.12.1 |
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