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

# my_awesome_model

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: 1.4723
- Accuracy: {'accuracy': 0.5292066259808196}
- Precision: {'precision': 0.5270248196529665}
- Recall: {'recall': 0.5128581630410899}
- F1: {'f1': 0.4836938691814141}

## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy                         | Precision                         | Recall                          | F1                          |
|:-------------:|:-----:|:----:|:---------------:|:--------------------------------:|:---------------------------------:|:-------------------------------:|:---------------------------:|
| 2.3362        | 1.0   | 1390 | 1.8634          | {'accuracy': 0.4119442022667829} | {'precision': 0.3707812573639524} | {'recall': 0.39448170731707316} | {'f1': 0.33817627082664936} |
| 1.5346        | 2.0   | 2780 | 1.4723          | {'accuracy': 0.5292066259808196} | {'precision': 0.5270248196529665} | {'recall': 0.5128581630410899}  | {'f1': 0.4836938691814141}  |


### Framework versions

- Transformers 4.41.1
- Pytorch 2.1.2
- Datasets 2.2.1
- Tokenizers 0.19.1