---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: XLMR_HASOC
  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. -->

# XLMR_HASOC

This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3081
- Accuracy: 0.6667
- F1: 0.6845

## 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: 1e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-05
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.7501        | 1.0   | 2100 | 0.7108          | 0.6756   | 0.7065 |
| 0.8911        | 2.0   | 4200 | 0.8944          | 0.6739   | 0.7022 |
| 0.9043        | 3.0   | 6300 | 1.3081          | 0.6667   | 0.6845 |


### Framework versions

- Transformers 4.27.4
- Pytorch 1.13.1+cu116
- Datasets 2.11.0
- Tokenizers 0.13.2