---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: new-test-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. -->

# new-test-model

This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0962
- Precision: 0.9704
- Recall: 0.9766
- F1: 0.9735
- Accuracy: 0.9791

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 151  | 0.1872          | 0.9295    | 0.9405 | 0.9349 | 0.9535   |
| No log        | 2.0   | 302  | 0.1417          | 0.9574    | 0.9652 | 0.9613 | 0.9679   |
| No log        | 3.0   | 453  | 0.1028          | 0.9676    | 0.9693 | 0.9684 | 0.9742   |
| 0.3037        | 4.0   | 604  | 0.1063          | 0.9676    | 0.9696 | 0.9686 | 0.9743   |
| 0.3037        | 5.0   | 755  | 0.0962          | 0.9704    | 0.9766 | 0.9735 | 0.9791   |


### Framework versions

- Transformers 4.18.0
- Pytorch 1.10.0+cu111
- Datasets 2.1.0
- Tokenizers 0.12.1