---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: AugWordNet_BERT_FPB_finetuned
  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. -->

# AugWordNet_BERT_FPB_finetuned

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3789
- Accuracy: 0.9097
- F1: 0.9100
- Precision: 0.9140
- Recall: 0.9097

## 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.8426        | 1.0   | 91   | 0.7693          | 0.6978   | 0.6777 | 0.6887    | 0.6978 |
| 0.4269        | 2.0   | 182  | 0.3264          | 0.8816   | 0.8803 | 0.8820    | 0.8816 |
| 0.3055        | 3.0   | 273  | 0.2990          | 0.8832   | 0.8838 | 0.8888    | 0.8832 |
| 0.2135        | 4.0   | 364  | 0.3049          | 0.9003   | 0.8998 | 0.9006    | 0.9003 |
| 0.1275        | 5.0   | 455  | 0.3764          | 0.8801   | 0.8786 | 0.8839    | 0.8801 |
| 0.1033        | 6.0   | 546  | 0.3393          | 0.9019   | 0.9007 | 0.9048    | 0.9019 |
| 0.0635        | 7.0   | 637  | 0.3829          | 0.9081   | 0.9079 | 0.9082    | 0.9081 |
| 0.0657        | 8.0   | 728  | 0.4759          | 0.8972   | 0.8958 | 0.8986    | 0.8972 |
| 0.0548        | 9.0   | 819  | 0.3789          | 0.9097   | 0.9100 | 0.9140    | 0.9097 |
| 0.0695        | 10.0  | 910  | 0.4797          | 0.8894   | 0.8876 | 0.8979    | 0.8894 |


### Framework versions

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