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--- |
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license: apache-2.0 |
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base_model: distilbert/distilbert-base-cased |
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tags: |
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- generated_from_trainer |
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metrics: |
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- precision |
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- recall |
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- f1 |
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- accuracy |
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model-index: |
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- name: distilbert-cased-lft |
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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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# distilbert-cased-lft |
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This model is a fine-tuned version of [distilbert/distilbert-base-cased](https://huggingface.co/distilbert/distilbert-base-cased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1017 |
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- Precision: 0.8722 |
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- Recall: 0.8905 |
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- F1: 0.8813 |
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- Accuracy: 0.9764 |
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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: 64 |
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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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- num_epochs: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
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|:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
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| No log | 0.4065 | 100 | 0.1106 | 0.8374 | 0.7969 | 0.8167 | 0.9647 | |
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| No log | 0.8130 | 200 | 0.0926 | 0.8242 | 0.8474 | 0.8356 | 0.9690 | |
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| No log | 1.2195 | 300 | 0.0898 | 0.8325 | 0.8671 | 0.8494 | 0.9704 | |
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| No log | 1.6260 | 400 | 0.0873 | 0.8591 | 0.8614 | 0.8602 | 0.9729 | |
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| 0.0943 | 2.0325 | 500 | 0.0829 | 0.8563 | 0.8765 | 0.8662 | 0.9740 | |
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| 0.0943 | 2.4390 | 600 | 0.0864 | 0.8656 | 0.8747 | 0.8701 | 0.9746 | |
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| 0.0943 | 2.8455 | 700 | 0.0842 | 0.8652 | 0.8761 | 0.8706 | 0.9746 | |
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| 0.0943 | 3.2520 | 800 | 0.0875 | 0.8627 | 0.8823 | 0.8724 | 0.9746 | |
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| 0.0943 | 3.6585 | 900 | 0.0887 | 0.8564 | 0.8829 | 0.8694 | 0.9744 | |
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| 0.0444 | 4.0650 | 1000 | 0.0875 | 0.8801 | 0.8797 | 0.8799 | 0.9763 | |
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| 0.0444 | 4.4715 | 1100 | 0.0944 | 0.8516 | 0.8901 | 0.8704 | 0.9746 | |
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| 0.0444 | 4.8780 | 1200 | 0.0906 | 0.8607 | 0.8891 | 0.8746 | 0.9752 | |
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| 0.0444 | 5.2846 | 1300 | 0.0934 | 0.8706 | 0.8896 | 0.8800 | 0.9765 | |
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| 0.0444 | 5.6911 | 1400 | 0.0914 | 0.8784 | 0.8862 | 0.8823 | 0.9765 | |
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| 0.0248 | 6.0976 | 1500 | 0.0918 | 0.8796 | 0.8896 | 0.8846 | 0.9772 | |
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| 0.0248 | 6.5041 | 1600 | 0.0960 | 0.8711 | 0.8916 | 0.8812 | 0.9765 | |
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| 0.0248 | 6.9106 | 1700 | 0.0970 | 0.8678 | 0.8876 | 0.8776 | 0.9763 | |
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| 0.0248 | 7.3171 | 1800 | 0.1008 | 0.8690 | 0.8887 | 0.8787 | 0.9759 | |
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| 0.0248 | 7.7236 | 1900 | 0.1012 | 0.8650 | 0.8926 | 0.8786 | 0.9759 | |
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| 0.0153 | 8.1301 | 2000 | 0.1002 | 0.8715 | 0.8921 | 0.8817 | 0.9762 | |
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| 0.0153 | 8.5366 | 2100 | 0.1003 | 0.8749 | 0.8889 | 0.8818 | 0.9763 | |
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| 0.0153 | 8.9431 | 2200 | 0.1015 | 0.8680 | 0.8917 | 0.8797 | 0.9760 | |
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| 0.0153 | 9.3496 | 2300 | 0.1015 | 0.8716 | 0.8882 | 0.8798 | 0.9764 | |
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| 0.0153 | 9.7561 | 2400 | 0.1017 | 0.8722 | 0.8905 | 0.8813 | 0.9764 | |
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### Framework versions |
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- Transformers 4.41.0 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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