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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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datasets:
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- amazon_reviews_multi
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model-index:
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- name: xlm-roberta-base-finetuned-marc
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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-roberta-base-finetuned-marc
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This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the amazon_reviews_multi dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.1299
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- Mae: 0.5619
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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: 1
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- eval_batch_size: 1
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 4
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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: 2
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Mae |
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|:-------------:|:-----:|:----:|:---------------:|:------:|
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| No log | 1.0 | 1182 | 1.1898 | 0.6 |
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| No log | 2.0 | 2364 | 1.1299 | 0.5619 |
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### Framework versions
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- Transformers 4.25.1
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- Pytorch 1.13.0+cu116
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- Datasets 2.8.0
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- Tokenizers 0.13.2
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