---
base_model: SALT-NLP/FLANG-BERT
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: FLANG-BERT_Synonym-wordnet
  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_Synonym-wordnet

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: 0.2403
- Accuracy: 0.9189
- F1: 0.9190
- Precision: 0.9194
- Recall: 0.9189

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.7933        | 1.0   | 91   | 0.7348          | 0.6880   | 0.6790 | 0.6972    | 0.6880 |
| 0.392         | 2.0   | 182  | 0.3757          | 0.8456   | 0.8461 | 0.8488    | 0.8456 |
| 0.2646        | 3.0   | 273  | 0.3044          | 0.8846   | 0.8839 | 0.8876    | 0.8846 |
| 0.1867        | 4.0   | 364  | 0.3522          | 0.8846   | 0.8846 | 0.8910    | 0.8846 |
| 0.1158        | 5.0   | 455  | 0.2403          | 0.9189   | 0.9190 | 0.9194    | 0.9189 |
| 0.1375        | 6.0   | 546  | 0.3255          | 0.9111   | 0.9105 | 0.9108    | 0.9111 |
| 0.1311        | 7.0   | 637  | 0.4090          | 0.8924   | 0.8930 | 0.9028    | 0.8924 |
| 0.1054        | 8.0   | 728  | 0.4269          | 0.9017   | 0.9015 | 0.9023    | 0.9017 |
| 0.0739        | 9.0   | 819  | 0.4098          | 0.9002   | 0.8992 | 0.9008    | 0.9002 |
| 0.0389        | 10.0  | 910  | 0.4411          | 0.9033   | 0.9030 | 0.9072    | 0.9033 |


### Framework versions

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