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

# HODravidianLangTech

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: 0.5859
- F1: 0.6908

## 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-06
- train_batch_size: 16
- eval_batch_size: 16
- seed: 1234
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log        | 1.0   | 100  | 0.6926          | 0.3377 |
| No log        | 2.0   | 200  | 0.6916          | 0.5490 |
| No log        | 3.0   | 300  | 0.6856          | 0.6050 |
| No log        | 4.0   | 400  | 0.6701          | 0.6287 |
| 0.6833        | 5.0   | 500  | 0.6601          | 0.6396 |
| 0.6833        | 6.0   | 600  | 0.6511          | 0.6466 |
| 0.6833        | 7.0   | 700  | 0.6447          | 0.6458 |
| 0.6833        | 8.0   | 800  | 0.6250          | 0.6560 |
| 0.6833        | 9.0   | 900  | 0.6113          | 0.6516 |
| 0.624         | 10.0  | 1000 | 0.6051          | 0.6658 |
| 0.624         | 11.0  | 1100 | 0.6075          | 0.6567 |
| 0.624         | 12.0  | 1200 | 0.6038          | 0.6671 |
| 0.624         | 13.0  | 1300 | 0.5997          | 0.6716 |
| 0.624         | 14.0  | 1400 | 0.5949          | 0.6805 |
| 0.5739        | 15.0  | 1500 | 0.5958          | 0.6885 |
| 0.5739        | 16.0  | 1600 | 0.5924          | 0.6905 |
| 0.5739        | 17.0  | 1700 | 0.5957          | 0.6875 |
| 0.5739        | 18.0  | 1800 | 0.5839          | 0.6976 |
| 0.5739        | 19.0  | 1900 | 0.5865          | 0.6908 |
| 0.5598        | 20.0  | 2000 | 0.5859          | 0.6908 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0