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--- |
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license: mit |
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base_model: indobenchmark/indobart |
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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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- precision |
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- recall |
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- f1 |
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model-index: |
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- name: bdc2024-indobartv2 |
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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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# bdc2024-indobartv2 |
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This model is a fine-tuned version of [indobenchmark/indobart](https://huggingface.co/indobenchmark/indobart) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1750 |
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- Accuracy: 0.9432 |
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- Balanced Accuracy: 0.8553 |
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- Precision: 0.9451 |
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- Recall: 0.9432 |
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- F1: 0.9424 |
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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: 16 |
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- eval_batch_size: 16 |
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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: 6 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Balanced Accuracy | Precision | Recall | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------------:|:---------:|:------:|:------:| |
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| No log | 1.0 | 271 | 0.7994 | 0.7664 | 0.4357 | 0.7110 | 0.7664 | 0.7293 | |
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| 0.8301 | 2.0 | 542 | 0.5663 | 0.8231 | 0.5167 | 0.8054 | 0.8231 | 0.7946 | |
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| 0.8301 | 3.0 | 813 | 0.3837 | 0.8690 | 0.6027 | 0.8607 | 0.8690 | 0.8564 | |
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| 0.4329 | 4.0 | 1084 | 0.2614 | 0.9192 | 0.7725 | 0.9192 | 0.9192 | 0.9161 | |
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| 0.4329 | 5.0 | 1355 | 0.2037 | 0.9345 | 0.8442 | 0.9345 | 0.9345 | 0.9330 | |
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| 0.2228 | 6.0 | 1626 | 0.1750 | 0.9432 | 0.8553 | 0.9451 | 0.9432 | 0.9424 | |
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### Framework versions |
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- Transformers 4.33.1 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.2 |
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- Tokenizers 0.13.3 |
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