---
base_model: SALT-NLP/FLANG-BERT
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: FLANG-BERT_roberta-base
  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. -->

# FLANG-BERT_roberta-base

This model is a fine-tuned version of [SALT-NLP/FLANG-BERT](https://huggingface.co/SALT-NLP/FLANG-BERT) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5101
- Accuracy: 0.8643
- F1: 0.8637
- Precision: 0.8638
- Recall: 0.8643

## 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: 0.0001
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 25

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.841         | 1.0   | 91   | 0.7542          | 0.6895   | 0.6505 | 0.7281    | 0.6895 |
| 0.4766        | 2.0   | 182  | 0.4469          | 0.8159   | 0.8161 | 0.8201    | 0.8159 |
| 0.3539        | 3.0   | 273  | 0.3916          | 0.8456   | 0.8459 | 0.8473    | 0.8456 |
| 0.2452        | 4.0   | 364  | 0.4667          | 0.8362   | 0.8348 | 0.8369    | 0.8362 |
| 0.1646        | 5.0   | 455  | 0.4408          | 0.8643   | 0.8636 | 0.8643    | 0.8643 |
| 0.1273        | 6.0   | 546  | 0.5101          | 0.8643   | 0.8637 | 0.8638    | 0.8643 |
| 0.1052        | 7.0   | 637  | 0.7249          | 0.8393   | 0.8369 | 0.8413    | 0.8393 |
| 0.0889        | 8.0   | 728  | 0.5791          | 0.8424   | 0.8413 | 0.8419    | 0.8424 |
| 0.0846        | 9.0   | 819  | 0.5522          | 0.8580   | 0.8576 | 0.8577    | 0.8580 |
| 0.0764        | 10.0  | 910  | 0.7277          | 0.8549   | 0.8549 | 0.8555    | 0.8549 |
| 0.1531        | 11.0  | 1001 | 0.6068          | 0.8424   | 0.8407 | 0.8441    | 0.8424 |


### Framework versions

- Transformers 4.37.0
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.1