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library_name: transformers
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: crowd_sourced_web_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. -->
# crowd_sourced_web_classifier
This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1845
- Accuracy: 0.5929
## 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: 0.002
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 4
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.5752 | 1.0 | 123 | 1.5979 | 0.3929 |
| 1.4761 | 2.0 | 246 | 1.3127 | 0.5738 |
| 1.101 | 3.0 | 369 | 1.2359 | 0.5667 |
| 1.1792 | 4.0 | 492 | 1.1845 | 0.5929 |
### Framework versions
- Transformers 4.57.2
- Pytorch 2.9.0
- Datasets 4.4.1
- Tokenizers 0.22.1
|