End of training
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- model.safetensors +1 -1
README.md
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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_v9
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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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# Zidan_model_output_v9
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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: 1.4760
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- Accuracy: 0.8
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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: 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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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| No log | 1.0 | 248 | 0.6499 | 0.7818 |
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| No log | 2.0 | 496 | 0.8322 | 0.7818 |
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| 0.7366 | 3.0 | 744 | 0.7805 | 0.8 |
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| 0.7366 | 4.0 | 992 | 1.1599 | 0.8182 |
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| 0.4101 | 5.0 | 1240 | 0.8254 | 0.8727 |
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| 0.4101 | 6.0 | 1488 | 0.9355 | 0.8364 |
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| 0.1646 | 7.0 | 1736 | 0.7034 | 0.9091 |
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| 0.1646 | 8.0 | 1984 | 0.8547 | 0.8545 |
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| 0.0927 | 9.0 | 2232 | 1.2842 | 0.8182 |
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| 0.0927 | 10.0 | 2480 | 1.2158 | 0.8364 |
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| 0.0457 | 11.0 | 2728 | 1.2863 | 0.8182 |
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| 0.0457 | 12.0 | 2976 | 1.4266 | 0.8182 |
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| 0.0383 | 13.0 | 3224 | 1.4670 | 0.8182 |
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| 0.0383 | 14.0 | 3472 | 1.4547 | 0.8182 |
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| 0.0221 | 15.0 | 3720 | 1.4760 | 0.8 |
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### Framework versions
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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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model.safetensors
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version https://git-lfs.github.com/spec/v1
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