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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-intent-label_smoothing
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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-intent-label_smoothing
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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: 2.5148
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- Accuracy: 0.8879
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- F1: 0.8879
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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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- label_smoothing_factor: 0.4
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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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| 3.3945 | 1.0 | 720 | 2.7175 | 0.7900 | 0.7900 |
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| 2.7629 | 2.0 | 1440 | 2.5660 | 0.8549 | 0.8549 |
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| 2.5143 | 3.0 | 2160 | 2.5389 | 0.8711 | 0.8711 |
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| 2.4678 | 4.0 | 2880 | 2.5172 | 0.8883 | 0.8883 |
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| 2.4187 | 5.0 | 3600 | 2.5148 | 0.8879 | 0.8879 |
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### Framework versions
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- Transformers 4.24.0
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- Pytorch 1.12.1+cu113
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- Datasets 2.7.0
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- Tokenizers 0.13.2
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