---
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: parsi-azma-test3
  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. -->

# parsi-azma-test3

This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6884
- F1: 0.5616

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- 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 | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.3751        | 1.0   | 200  | 0.4398          | 0.5558 |
| 0.4578        | 2.0   | 400  | 0.5175          | 0.5586 |
| 0.3447        | 3.0   | 600  | 0.4170          | 0.5654 |
| 0.3003        | 4.0   | 800  | 0.5484          | 0.5658 |
| 0.2291        | 5.0   | 1000 | 0.6582          | 0.5184 |
| 0.3479        | 6.0   | 1200 | 0.5209          | 0.5591 |
| 0.4688        | 7.0   | 1400 | 0.6091          | 0.5725 |
| 0.1028        | 8.0   | 1600 | 0.6661          | 0.5692 |
| 0.1301        | 9.0   | 1800 | 0.6655          | 0.5636 |
| 0.2515        | 10.0  | 2000 | 0.6884          | 0.5616 |


### Framework versions

- Transformers 4.32.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.3
- Tokenizers 0.13.3