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---
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library_name: transformers
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license: mit
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base_model: FacebookAI/xlm-roberta-large
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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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model-index:
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- name: phobert_product_classifier
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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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# phobert_product_classifier
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This model is a fine-tuned version of [FacebookAI/xlm-roberta-large](https://huggingface.co/FacebookAI/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: 1.0903
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- Accuracy: 0.8186
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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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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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 |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 1.6217 | 1.0 | 979 | 0.8925 | 0.7543 |
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| 0.7822 | 2.0 | 1958 | 0.8323 | 0.7783 |
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| 0.5761 | 3.0 | 2937 | 0.7874 | 0.7862 |
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| 0.4518 | 4.0 | 3916 | 0.7734 | 0.8031 |
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| 0.3516 | 5.0 | 4895 | 0.8313 | 0.8026 |
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| 0.2591 | 6.0 | 5874 | 0.8730 | 0.8095 |
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| 0.1789 | 7.0 | 6853 | 0.9955 | 0.8089 |
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| 0.1235 | 8.0 | 7832 | 1.0196 | 0.8179 |
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| 0.0832 | 9.0 | 8811 | 1.0750 | 0.8174 |
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| 0.0644 | 10.0 | 9790 | 1.0903 | 0.8186 |
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### Framework versions
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- Transformers 4.48.0
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- Pytorch 2.5.1+cu124
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- Datasets 2.21.0
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- Tokenizers 0.21.0
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