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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: xlm-r-base-amazon-massive-domain
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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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# xlm-r-base-amazon-massive-domain
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This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.3788
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- Accuracy: 0.9213
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- F1: 0.9213
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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: 2e-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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- num_epochs: 5
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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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| 1.382 | 1.0 | 720 | 0.4533 | 0.8795 | 0.8795 |
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| 0.4598 | 2.0 | 1440 | 0.3448 | 0.9026 | 0.9026 |
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| 0.2547 | 3.0 | 2160 | 0.3762 | 0.9065 | 0.9065 |
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| 0.1986 | 4.0 | 2880 | 0.3748 | 0.9139 | 0.9139 |
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| 0.1358 | 5.0 | 3600 | 0.3788 | 0.9213 | 0.9213 |
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### Framework versions
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- Transformers 4.22.1
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- Pytorch 1.12.1+cu113
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- Datasets 2.5.1
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- Tokenizers 0.12.1
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