---
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
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# 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: 1.4363
- Accuracy: 0.6226

## 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: 5e-05
- 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: 6
- label_smoothing_factor: 0.1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 124  | 1.6580          | 0.4835   |
| No log        | 2.0   | 248  | 1.6012          | 0.5118   |
| No log        | 3.0   | 372  | 1.4782          | 0.5731   |
| No log        | 4.0   | 496  | 1.4082          | 0.5991   |
| 1.5207        | 5.0   | 620  | 1.3994          | 0.6392   |
| 1.5207        | 6.0   | 744  | 1.4363          | 0.6226   |


### Framework versions

- Transformers 4.57.1
- Pytorch 2.9.0
- Datasets 4.4.1
- Tokenizers 0.22.1