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---
library_name: transformers
license: mit
base_model: FacebookAI/xlm-roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: phobert_product_classifier
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# phobert_product_classifier
This model is a fine-tuned version of [FacebookAI/xlm-roberta-large](https://huggingface.co/FacebookAI/xlm-roberta-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0903
- Accuracy: 0.8186
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.6217 | 1.0 | 979 | 0.8925 | 0.7543 |
| 0.7822 | 2.0 | 1958 | 0.8323 | 0.7783 |
| 0.5761 | 3.0 | 2937 | 0.7874 | 0.7862 |
| 0.4518 | 4.0 | 3916 | 0.7734 | 0.8031 |
| 0.3516 | 5.0 | 4895 | 0.8313 | 0.8026 |
| 0.2591 | 6.0 | 5874 | 0.8730 | 0.8095 |
| 0.1789 | 7.0 | 6853 | 0.9955 | 0.8089 |
| 0.1235 | 8.0 | 7832 | 1.0196 | 0.8179 |
| 0.0832 | 9.0 | 8811 | 1.0750 | 0.8174 |
| 0.0644 | 10.0 | 9790 | 1.0903 | 0.8186 |
### Framework versions
- Transformers 4.48.0
- Pytorch 2.5.1+cu124
- Datasets 2.21.0
- Tokenizers 0.21.0
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