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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-multilingual-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-multilingual-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: 0.5146
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- Accuracy: 0.8579
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- F1: 0.8583
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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: 8
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- seed: 42
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- gradient_accumulation_steps: 16
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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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| 0.4787 | 0.5 | 1574 | 0.4285 | 0.8364 | 0.8358 |
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| 0.4418 | 1.0 | 3148 | 0.4040 | 0.8494 | 0.8496 |
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| 0.3942 | 1.5 | 4722 | 0.3971 | 0.8514 | 0.8505 |
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| 0.3722 | 2.0 | 6296 | 0.3835 | 0.8579 | 0.8581 |
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| 0.3206 | 2.5 | 7870 | 0.4139 | 0.8587 | 0.8586 |
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| 0.3229 | 3.0 | 9444 | 0.4033 | 0.8600 | 0.8602 |
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| 0.2616 | 3.5 | 11018 | 0.4457 | 0.8585 | 0.8591 |
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| 0.2862 | 4.0 | 12592 | 0.4319 | 0.8619 | 0.8617 |
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| 0.2261 | 4.5 | 14166 | 0.4859 | 0.8562 | 0.8570 |
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| 0.2215 | 5.0 | 15740 | 0.4728 | 0.8592 | 0.8599 |
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| 0.1874 | 5.5 | 17314 | 0.5146 | 0.8579 | 0.8583 |
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### Framework versions
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- Transformers 4.26.1
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- Pytorch 1.13.1+cu117
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- Datasets 2.2.0
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- Tokenizers 0.13.2
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