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praysimanjuntak/distilbert-cased-lft

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README.md ADDED
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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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+
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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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+
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+ # distilbert-cased-lft
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+
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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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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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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+
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+ ### Training results
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+
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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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+
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+
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+ ### Framework versions
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+
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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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+ "model_type": "distilbert",
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+ "n_layers": 6,
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+ "output_past": true,
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