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--- |
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license: apache-2.0 |
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base_model: LazarusNLP/IndoNanoT5-base |
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tags: |
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- generated_from_trainer |
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language: |
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- ind |
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datasets: |
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- GEM/indonlg |
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metrics: |
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- f1 |
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model-index: |
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- name: IndoNanoT5-base-TyDiQA |
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results: |
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- task: |
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name: Sequence-to-sequence Language Modeling |
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type: text2text-generation |
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dataset: |
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name: indonlg |
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type: indonlg |
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config: question_answering |
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split: test |
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args: question_answering |
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metrics: |
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- name: F1 |
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type: f1 |
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value: 72.19688326266134 |
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- name: EM |
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type: em |
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value: 58.9474 |
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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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# LazarusNLP/IndoNanoT5-base-TyDiQA |
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This model is a fine-tuned version of [LazarusNLP/IndoNanoT5-base](https://huggingface.co/LazarusNLP/IndoNanoT5-base) on the indonlg dataset. |
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It achieves the following results on the evaluation set: |
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- Exact: 58.9474 |
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- F1: 72.1969 |
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- Total: 855 |
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- Hasans Exact: 58.9474 |
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- Hasans F1: 72.1969 |
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- Hasans Total: 855 |
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- Best Exact: 58.9474 |
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- Best Exact Thresh: 0.0 |
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- Best F1: 72.1969 |
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- Best F1 Thresh: 0.0 |
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- Loss: 0.1283 |
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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: 8 |
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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: 50 |
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### Training results |
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| Training Loss | Epoch | Step | Exact | F1 | Total | Hasans Exact | Hasans F1 | Hasans Total | Best Exact | Best Exact Thresh | Best F1 | Best F1 Thresh | Validation Loss | |
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|:-------------:|:-----:|:----:|:-------:|:-------:|:-----:|:------------:|:---------:|:------------:|:----------:|:-----------------:|:-------:|:--------------:|:---------------:| |
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| 1.9173 | 1.0 | 606 | 45.1327 | 63.8499 | 565 | 45.1327 | 63.8499 | 565 | 45.1327 | 0.0 | 63.8499 | 0.0 | 0.1147 | |
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| 0.1971 | 2.0 | 1212 | 50.4425 | 68.7240 | 565 | 50.4425 | 68.7240 | 565 | 50.4425 | 0.0 | 68.7240 | 0.0 | 0.1025 | |
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| 0.1475 | 3.0 | 1818 | 53.8053 | 71.0124 | 565 | 53.8053 | 71.0124 | 565 | 53.8053 | 0.0 | 71.0124 | 0.0 | 0.0992 | |
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| 0.1175 | 4.0 | 2424 | 53.6283 | 71.1353 | 565 | 53.6283 | 71.1353 | 565 | 53.6283 | 0.0 | 71.1353 | 0.0 | 0.1008 | |
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| 0.0814 | 5.0 | 3030 | 53.4513 | 71.0439 | 565 | 53.4513 | 71.0439 | 565 | 53.4513 | 0.0 | 71.0439 | 0.0 | 0.1040 | |
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| 0.0665 | 6.0 | 3636 | 54.1593 | 71.5788 | 565 | 54.1593 | 71.5788 | 565 | 54.1593 | 0.0 | 71.5788 | 0.0 | 0.1051 | |
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| 0.0555 | 7.0 | 4242 | 54.8673 | 72.4372 | 565 | 54.8673 | 72.4372 | 565 | 54.8673 | 0.0 | 72.4372 | 0.0 | 0.1137 | |
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| 0.0483 | 8.0 | 4848 | 56.2832 | 72.3749 | 565 | 56.2832 | 72.3749 | 565 | 56.2832 | 0.0 | 72.3749 | 0.0 | 0.1188 | |
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| 0.0416 | 9.0 | 5454 | 55.5752 | 72.2892 | 565 | 55.5752 | 72.2892 | 565 | 55.5752 | 0.0 | 72.2892 | 0.0 | 0.1154 | |
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| 0.031 | 10.0 | 6060 | 55.0442 | 71.8127 | 565 | 55.0442 | 71.8127 | 565 | 55.0442 | 0.0 | 71.8127 | 0.0 | 0.1312 | |
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| 0.0278 | 11.0 | 6666 | 55.7522 | 73.4756 | 565 | 55.7522 | 73.4756 | 565 | 55.7522 | 0.0 | 73.4756 | 0.0 | 0.1253 | |
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| 0.0257 | 12.0 | 7272 | 55.7522 | 73.0958 | 565 | 55.7522 | 73.0958 | 565 | 55.7522 | 0.0 | 73.0958 | 0.0 | 0.1292 | |
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| 0.023 | 13.0 | 7878 | 56.2832 | 73.3269 | 565 | 56.2832 | 73.3269 | 565 | 56.2832 | 0.0 | 73.3269 | 0.0 | 0.1271 | |
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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 2.16.1 |
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- Tokenizers 0.15.1 |
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