ZidanAf commited on
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365a2bd
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Training in progress, epoch 1

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README.md ADDED
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+ ---
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+ license: mit
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+ base_model: indolem/indobert-base-uncased
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: Zidan_model_output_v12
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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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+ # Zidan_model_output_v12
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+
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+ This model is a fine-tuned version of [indolem/indobert-base-uncased](https://huggingface.co/indolem/indobert-base-uncased) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.8981
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+ - Accuracy: 0.5818
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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: 1e-06
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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: 15
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | No log | 1.0 | 220 | 1.0490 | 0.5091 |
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+ | No log | 2.0 | 440 | 0.9815 | 0.5182 |
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+ | 1.0255 | 3.0 | 660 | 0.9462 | 0.5455 |
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+ | 1.0255 | 4.0 | 880 | 0.9429 | 0.5545 |
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+ | 0.862 | 5.0 | 1100 | 0.9189 | 0.5636 |
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+ | 0.862 | 6.0 | 1320 | 0.9143 | 0.5727 |
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+ | 0.7694 | 7.0 | 1540 | 0.9051 | 0.5545 |
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+ | 0.7694 | 8.0 | 1760 | 0.9033 | 0.5545 |
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+ | 0.7694 | 9.0 | 1980 | 0.9024 | 0.5636 |
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+ | 0.7092 | 10.0 | 2200 | 0.9031 | 0.5636 |
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+ | 0.7092 | 11.0 | 2420 | 0.9067 | 0.5909 |
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+ | 0.65 | 12.0 | 2640 | 0.8994 | 0.5636 |
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+ | 0.65 | 13.0 | 2860 | 0.8963 | 0.5727 |
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+ | 0.63 | 14.0 | 3080 | 0.8971 | 0.5727 |
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+ | 0.63 | 15.0 | 3300 | 0.8981 | 0.5818 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.41.2
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+ - Pytorch 2.3.0+cu121
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+ - Datasets 2.20.0
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+ - Tokenizers 0.19.1
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+ "problem_type": "single_label_classification",
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+ "torch_dtype": "float32",
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