Ramadhiana
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---
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