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--- |
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license: mit |
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base_model: LazarusNLP/NusaBERT-base |
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tags: |
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- generated_from_trainer |
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datasets: |
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- indonlu |
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metrics: |
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- f1 |
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model-index: |
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- name: NusaBERT-base-EmoT |
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results: |
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- task: |
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name: Text Classification |
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type: text-classification |
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dataset: |
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name: indonlu |
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type: indonlu |
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config: emot |
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split: validation |
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args: emot |
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metrics: |
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- name: F1 |
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type: f1 |
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value: 0.7275 |
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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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# NusaBERT-base-EmoT |
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This model is a fine-tuned version of [LazarusNLP/NusaBERT-base](https://huggingface.co./LazarusNLP/NusaBERT-base) on the indonlu dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.9150 |
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- F1: 0.7275 |
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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: 1e-05 |
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- train_batch_size: 32 |
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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: cosine |
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- num_epochs: 100 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:------:| |
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| No log | 1.0 | 111 | 1.1739 | 0.5257 | |
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| No log | 2.0 | 222 | 0.8140 | 0.7112 | |
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| No log | 3.0 | 333 | 0.7669 | 0.7269 | |
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| No log | 4.0 | 444 | 0.7582 | 0.7291 | |
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| 0.8669 | 5.0 | 555 | 0.8084 | 0.7331 | |
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| 0.8669 | 6.0 | 666 | 0.7993 | 0.7351 | |
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| 0.8669 | 7.0 | 777 | 0.8812 | 0.7427 | |
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| 0.8669 | 8.0 | 888 | 0.9146 | 0.7477 | |
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| 0.8669 | 9.0 | 999 | 1.0099 | 0.7473 | |
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| 0.2674 | 10.0 | 1110 | 1.1308 | 0.7285 | |
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| 0.2674 | 11.0 | 1221 | 1.1548 | 0.7382 | |
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| 0.2674 | 12.0 | 1332 | 1.2518 | 0.7318 | |
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| 0.2674 | 13.0 | 1443 | 1.4757 | 0.7084 | |
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### Framework versions |
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- Transformers 4.37.2 |
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- Pytorch 2.2.0+cu118 |
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- Datasets 2.17.1 |
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- Tokenizers 0.15.1 |
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