---
library_name: transformers
license: mit
base_model: FacebookAI/xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: job_classifier_model_v2
  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. -->

# job_classifier_model_v2

This model is a fine-tuned version of [FacebookAI/xlm-roberta-base](https://huggingface.co/FacebookAI/xlm-roberta-base) on the Job dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0491
- Accuracy: 0.9942
- Precision: 0.9930
- Recall: 0.9953
- F1: 0.9942

## 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: 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: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.1122        | 1.0   | 859  | 0.0529          | 0.9907   | 0.9930    | 0.9883 | 0.9907 |
| 0.0325        | 2.0   | 1718 | 0.0338          | 0.9953   | 0.9930    | 0.9977 | 0.9953 |
| 0.0088        | 3.0   | 2577 | 0.0491          | 0.9942   | 0.9930    | 0.9953 | 0.9942 |


### Framework versions

- Transformers 4.56.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.0