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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: xlm-roberta-large_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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# xlm-roberta-large_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: 1.3981
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- Accuracy: 0.8169
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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: 32
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- eval_batch_size: 32
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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: 20
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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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| No log | 1.0 | 490 | 0.8869 | 0.7423 |
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| 1.3297 | 2.0 | 980 | 0.7796 | 0.7798 |
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| 0.7265 | 3.0 | 1470 | 0.7592 | 0.7872 |
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| 0.5509 | 4.0 | 1960 | 0.8112 | 0.7949 |
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| 0.4258 | 5.0 | 2450 | 0.8498 | 0.7875 |
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| 0.3307 | 6.0 | 2940 | 0.8326 | 0.8036 |
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| 0.2702 | 7.0 | 3430 | 0.8833 | 0.8066 |
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| 0.2078 | 8.0 | 3920 | 0.9260 | 0.8066 |
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| 0.1571 | 9.0 | 4410 | 0.9800 | 0.8087 |
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| 0.1242 | 10.0 | 4900 | 1.0725 | 0.8043 |
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| 0.0962 | 11.0 | 5390 | 1.2147 | 0.7946 |
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| 0.0857 | 12.0 | 5880 | 1.1705 | 0.8123 |
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| 0.0667 | 13.0 | 6370 | 1.2551 | 0.8041 |
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| 0.052 | 14.0 | 6860 | 1.2762 | 0.8184 |
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| 0.0414 | 15.0 | 7350 | 1.3442 | 0.8115 |
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| 0.0313 | 16.0 | 7840 | 1.3510 | 0.8130 |
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| 0.0247 | 17.0 | 8330 | 1.3754 | 0.8133 |
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| 0.0158 | 18.0 | 8820 | 1.3915 | 0.8135 |
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| 0.0162 | 19.0 | 9310 | 1.3975 | 0.8186 |
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| 0.0109 | 20.0 | 9800 | 1.3981 | 0.8169 |
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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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