---
license: mit
base_model: FacebookAI/xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: XMLRoberta_Dataset9kMeta
  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. -->

[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/ronton/huggingface/runs/nd99qd0g)
# XMLRoberta_Dataset9kMeta

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: 0.2475
- Accuracy: 0.9498
- F1: 0.9499

## 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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|
| No log        | 1.6461 | 200  | 0.2426          | 0.9319   | 0.9192 |
| 0.4716        | 3.2922 | 400  | 0.2306          | 0.9226   | 0.9152 |
| 0.1801        | 4.9383 | 600  | 0.2223          | 0.9464   | 0.9457 |
| 0.118         | 6.5844 | 800  | 0.2062          | 0.9498   | 0.9492 |
| 0.0819        | 8.2305 | 1000 | 0.2399          | 0.9498   | 0.9504 |
| 0.0819        | 9.8765 | 1200 | 0.2475          | 0.9498   | 0.9499 |


### Framework versions

- Transformers 4.43.1
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1