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--- |
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license: apache-2.0 |
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base_model: Toshifumi/distilbert-base-multilingual-cased-finetuned-emotion |
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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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- 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: indonesian-distilbert-base-cased-finetuned-indonlu |
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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: Accuracy |
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type: accuracy |
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value: 0.6113636363636363 |
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- name: Precision |
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type: precision |
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value: 0.6057688190944959 |
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- name: Recall |
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type: recall |
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value: 0.6113636363636363 |
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- name: F1 |
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type: f1 |
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value: 0.6068671444135532 |
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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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# indonesian-distilbert-base-cased-finetuned-indonlu |
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This model is a fine-tuned version of [Toshifumi/distilbert-base-multilingual-cased-finetuned-emotion](https://huggingface.co/Toshifumi/distilbert-base-multilingual-cased-finetuned-emotion) on the indonlu dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.1300 |
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- Accuracy: 0.6114 |
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- Precision: 0.6058 |
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- Recall: 0.6114 |
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- F1: 0.6069 |
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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: 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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- lr_scheduler_warmup_ratio: 0.01 |
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- num_epochs: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
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| No log | 1.0 | 221 | 1.2623 | 0.475 | 0.4817 | 0.475 | 0.4458 | |
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| No log | 2.0 | 442 | 1.0937 | 0.55 | 0.5555 | 0.55 | 0.5444 | |
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| 1.2289 | 3.0 | 663 | 1.0749 | 0.5886 | 0.6003 | 0.5886 | 0.5898 | |
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| 1.2289 | 4.0 | 884 | 1.0836 | 0.5818 | 0.6019 | 0.5818 | 0.5800 | |
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| 0.7857 | 5.0 | 1105 | 1.1300 | 0.6114 | 0.6058 | 0.6114 | 0.6069 | |
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| 0.7857 | 6.0 | 1326 | 1.1595 | 0.6 | 0.5996 | 0.6 | 0.5984 | |
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| 0.5288 | 7.0 | 1547 | 1.1767 | 0.6 | 0.5986 | 0.6 | 0.5958 | |
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| 0.5288 | 8.0 | 1768 | 1.2195 | 0.6 | 0.5969 | 0.6 | 0.5952 | |
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| 0.5288 | 9.0 | 1989 | 1.2422 | 0.5932 | 0.5915 | 0.5932 | 0.5909 | |
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| 0.3685 | 10.0 | 2210 | 1.2406 | 0.5841 | 0.5842 | 0.5841 | 0.5830 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.17.1 |
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- Tokenizers 0.15.2 |
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