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--- |
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base_model: google-bert/bert-base-uncased |
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library_name: transformers |
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license: apache-2.0 |
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metrics: |
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- accuracy |
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- f1 |
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- precision |
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- recall |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: bert-base-uncased-intent-booking |
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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-base-uncased-intent-booking |
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This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/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: 2.1797 |
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- Accuracy: 0.1937 |
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- F1: 0.1715 |
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- Precision: 0.3099 |
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- Recall: 0.1937 |
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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: 5e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 64 |
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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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- lr_scheduler_warmup_steps: 64 |
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- num_epochs: 20 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| |
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| 2.3533 | 1.0 | 65 | 2.3007 | 0.0946 | 0.0338 | 0.0281 | 0.0946 | |
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| 2.2868 | 2.0 | 130 | 2.1968 | 0.1351 | 0.0632 | 0.0472 | 0.1351 | |
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| 2.2299 | 3.0 | 195 | 2.1730 | 0.1847 | 0.1151 | 0.1020 | 0.1847 | |
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| 2.1909 | 4.0 | 260 | 2.1719 | 0.1937 | 0.1687 | 0.3112 | 0.1937 | |
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| 2.1657 | 5.0 | 325 | 2.1376 | 0.2027 | 0.1567 | 0.2069 | 0.2027 | |
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| 2.1437 | 6.0 | 390 | 2.1459 | 0.1757 | 0.1461 | 0.1909 | 0.1757 | |
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| 2.1342 | 7.0 | 455 | 2.1581 | 0.1667 | 0.1418 | 0.2867 | 0.1667 | |
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| 2.1025 | 8.0 | 520 | 2.1425 | 0.1892 | 0.1504 | 0.2449 | 0.1892 | |
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| 2.0749 | 9.0 | 585 | 2.1277 | 0.1847 | 0.1641 | 0.3096 | 0.1847 | |
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| 2.0482 | 10.0 | 650 | 2.1283 | 0.2117 | 0.1895 | 0.3519 | 0.2117 | |
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| 2.0654 | 11.0 | 715 | 2.1253 | 0.2117 | 0.1886 | 0.3004 | 0.2117 | |
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| 2.0443 | 12.0 | 780 | 2.1200 | 0.1937 | 0.1770 | 0.2982 | 0.1937 | |
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| 2.0345 | 13.0 | 845 | 2.1252 | 0.1937 | 0.1791 | 0.3098 | 0.1937 | |
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| 2.0148 | 14.0 | 910 | 2.1113 | 0.1982 | 0.1783 | 0.2804 | 0.1982 | |
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| 2.0112 | 15.0 | 975 | 2.1372 | 0.1892 | 0.1702 | 0.2746 | 0.1892 | |
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| 2.0022 | 16.0 | 1040 | 2.1254 | 0.1892 | 0.1696 | 0.2710 | 0.1892 | |
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| 1.9913 | 17.0 | 1105 | 2.1221 | 0.1892 | 0.1696 | 0.2710 | 0.1892 | |
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| 1.9827 | 18.0 | 1170 | 2.1090 | 0.1982 | 0.1758 | 0.2910 | 0.1982 | |
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| 1.9871 | 19.0 | 1235 | 2.1111 | 0.1982 | 0.1789 | 0.2756 | 0.1982 | |
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| 1.9824 | 20.0 | 1300 | 2.1132 | 0.1892 | 0.1705 | 0.2665 | 0.1892 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 3.0.1 |
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- Tokenizers 0.19.1 |
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