---
library_name: transformers
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: xml-roberta-large-v3
  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. -->

# xml-roberta-large-v3

This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0792
- Precision: 0.9448
- Recall: 0.9726
- F1: 0.9585
- Accuracy: 0.9806

## 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
- gradient_accumulation_steps: 3
- total_train_batch_size: 48
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.3722        | 1.0   | 204  | 0.2039          | 0.8490    | 0.8680 | 0.8584 | 0.9440   |
| 0.1353        | 2.0   | 408  | 0.0930          | 0.9324    | 0.9626 | 0.9473 | 0.9759   |
| 0.0969        | 3.0   | 612  | 0.0869          | 0.9407    | 0.9684 | 0.9543 | 0.9776   |
| 0.0785        | 4.0   | 816  | 0.0818          | 0.9411    | 0.9729 | 0.9568 | 0.9793   |
| 0.0498        | 5.0   | 1020 | 0.0792          | 0.9448    | 0.9726 | 0.9585 | 0.9806   |


### Framework versions

- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3