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update model card README.md
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README.md
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---
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license: mit
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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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- f1
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model-index:
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- name: fine-tuned-NLI-indonli-with-xlm-roberta-large
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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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# fine-tuned-NLI-indonli-with-xlm-roberta-large
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This model is a fine-tuned version of [xlm-roberta-large](https://huggingface.co/xlm-roberta-large) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4642
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- Accuracy: 0.8521
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- F1: 0.8520
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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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- gradient_accumulation_steps: 8
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- total_train_batch_size: 128
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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: 10
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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| 1.0772 | 0.5 | 40 | 1.0981 | 0.3473 | 0.1940 |
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| 1.1047 | 0.99 | 80 | 1.0967 | 0.3878 | 0.2972 |
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| 1.1123 | 1.5 | 120 | 0.7637 | 0.7128 | 0.7099 |
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| 0.8279 | 1.99 | 160 | 0.5739 | 0.7870 | 0.7848 |
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| 0.5873 | 2.5 | 200 | 0.5059 | 0.8229 | 0.8232 |
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| 0.5873 | 2.99 | 240 | 0.5047 | 0.8234 | 0.8258 |
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| 0.5418 | 3.5 | 280 | 0.4696 | 0.8380 | 0.8381 |
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| 0.4472 | 3.99 | 320 | 0.4415 | 0.8457 | 0.8458 |
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| 0.4041 | 4.5 | 360 | 0.4622 | 0.8521 | 0.8522 |
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| 0.3767 | 4.99 | 400 | 0.4435 | 0.8489 | 0.8498 |
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| 0.3767 | 5.5 | 440 | 0.4731 | 0.8498 | 0.8503 |
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| 0.3307 | 5.99 | 480 | 0.4642 | 0.8521 | 0.8520 |
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### Framework versions
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- Transformers 4.26.1
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- Pytorch 2.0.1+cu117
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- Datasets 2.2.0
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- Tokenizers 0.13.3
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