---
license: mit
base_model: FacebookAI/xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: XMLRoberta_70KURL
  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. -->

# XMLRoberta_70KURL

This model is a fine-tuned version of [FacebookAI/xlm-roberta-base](https://huggingface.co/FacebookAI/xlm-roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4150
- Accuracy: 0.9408
- F1: 0.9448

## 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: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2150
- num_epochs: 20

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-------:|:----:|:---------------:|:--------:|:------:|
| No log        | 0.4651  | 200  | 0.4701          | 0.8955   | 0.8673 |
| No log        | 0.9302  | 400  | 0.1893          | 0.9359   | 0.9368 |
| No log        | 1.3953  | 600  | 0.2241          | 0.9128   | 0.9192 |
| No log        | 1.8605  | 800  | 0.2777          | 0.8848   | 0.8984 |
| 0.382         | 2.3256  | 1000 | 0.1388          | 0.9504   | 0.9525 |
| 0.382         | 2.7907  | 1200 | 0.1028          | 0.9694   | 0.9701 |
| 0.382         | 3.2558  | 1400 | 0.1413          | 0.9557   | 0.9579 |
| 0.382         | 3.7209  | 1600 | 0.0929          | 0.9718   | 0.9722 |
| 0.1521        | 4.1860  | 1800 | 0.1008          | 0.9695   | 0.9702 |
| 0.1521        | 4.6512  | 2000 | 0.1939          | 0.9238   | 0.9306 |
| 0.1521        | 5.1163  | 2200 | 0.1550          | 0.9401   | 0.9443 |
| 0.1521        | 5.5814  | 2400 | 0.0813          | 0.9744   | 0.9750 |
| 0.1044        | 6.0465  | 2600 | 0.2088          | 0.9193   | 0.9267 |
| 0.1044        | 6.5116  | 2800 | 0.1343          | 0.9523   | 0.9548 |
| 0.1044        | 6.9767  | 3000 | 0.2172          | 0.9219   | 0.9289 |
| 0.1044        | 7.4419  | 3200 | 0.1097          | 0.9656   | 0.9668 |
| 0.1044        | 7.9070  | 3400 | 0.3044          | 0.9147   | 0.9230 |
| 0.0762        | 8.3721  | 3600 | 0.2122          | 0.9283   | 0.9341 |
| 0.0762        | 8.8372  | 3800 | 0.1430          | 0.9532   | 0.9556 |
| 0.0762        | 9.3023  | 4000 | 0.2332          | 0.9312   | 0.9368 |
| 0.0762        | 9.7674  | 4200 | 0.2167          | 0.9297   | 0.9353 |
| 0.0564        | 10.2326 | 4400 | 0.1904          | 0.9475   | 0.9506 |
| 0.0564        | 10.6977 | 4600 | 0.2916          | 0.9196   | 0.9270 |
| 0.0564        | 11.1628 | 4800 | 0.2317          | 0.9451   | 0.9484 |
| 0.0564        | 11.6279 | 5000 | 0.2430          | 0.9475   | 0.9503 |
| 0.042         | 12.0930 | 5200 | 0.4035          | 0.9248   | 0.9315 |
| 0.042         | 12.5581 | 5400 | 0.3060          | 0.9352   | 0.9398 |
| 0.042         | 13.0233 | 5600 | 0.2894          | 0.9359   | 0.9407 |
| 0.042         | 13.4884 | 5800 | 0.2804          | 0.9439   | 0.9474 |
| 0.042         | 13.9535 | 6000 | 0.2941          | 0.9456   | 0.9490 |
| 0.0316        | 14.4186 | 6200 | 0.3211          | 0.9424   | 0.9460 |
| 0.0316        | 14.8837 | 6400 | 0.3453          | 0.9371   | 0.9416 |
| 0.0316        | 15.3488 | 6600 | 0.2587          | 0.9548   | 0.9569 |
| 0.0316        | 15.8140 | 6800 | 0.3433          | 0.9432   | 0.9468 |
| 0.025         | 16.2791 | 7000 | 0.3454          | 0.9416   | 0.9455 |
| 0.025         | 16.7442 | 7200 | 0.2977          | 0.9450   | 0.9484 |
| 0.025         | 17.2093 | 7400 | 0.3622          | 0.9452   | 0.9486 |
| 0.025         | 17.6744 | 7600 | 0.3035          | 0.9550   | 0.9572 |
| 0.0196        | 18.1395 | 7800 | 0.3588          | 0.9464   | 0.9496 |
| 0.0196        | 18.6047 | 8000 | 0.3714          | 0.9467   | 0.9500 |
| 0.0196        | 19.0698 | 8200 | 0.4517          | 0.9341   | 0.9391 |
| 0.0196        | 19.5349 | 8400 | 0.4078          | 0.9411   | 0.9451 |
| 0.0148        | 20.0    | 8600 | 0.4150          | 0.9408   | 0.9448 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1