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  2. model.safetensors +1 -1
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_v10
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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_v10
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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: 0.7422
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+ - Accuracy: 0.7455
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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 | 248 | 1.0211 | 0.5273 |
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+ | No log | 2.0 | 496 | 0.9519 | 0.6727 |
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+ | 1.0031 | 3.0 | 744 | 0.8800 | 0.6545 |
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+ | 1.0031 | 4.0 | 992 | 0.8159 | 0.6909 |
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+ | 0.8477 | 5.0 | 1240 | 0.8053 | 0.6909 |
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+ | 0.8477 | 6.0 | 1488 | 0.8047 | 0.7455 |
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+ | 0.7504 | 7.0 | 1736 | 0.7551 | 0.7455 |
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+ | 0.7504 | 8.0 | 1984 | 0.7315 | 0.7273 |
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+ | 0.6811 | 9.0 | 2232 | 0.7451 | 0.7273 |
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+ | 0.6811 | 10.0 | 2480 | 0.7716 | 0.7273 |
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+ | 0.6299 | 11.0 | 2728 | 0.7615 | 0.7636 |
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+ | 0.6299 | 12.0 | 2976 | 0.7530 | 0.7455 |
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+ | 0.5932 | 13.0 | 3224 | 0.7416 | 0.7455 |
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+ | 0.5932 | 14.0 | 3472 | 0.7476 | 0.7455 |
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+ | 0.5699 | 15.0 | 3720 | 0.7422 | 0.7455 |
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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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