---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: atco2_test_set_1h
  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. -->

# atco2_test_set_1h

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: 1.4282
- Precision: 0.6195
- Recall: 0.7071
- F1: 0.6604
- Accuracy: 0.8182

## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 3000

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 125.0 | 500  | 0.8692          | 0.6396    | 0.7172 | 0.6762 | 0.8307   |
| 0.2158        | 250.0 | 1000 | 1.0074          | 0.5702    | 0.6970 | 0.6273 | 0.8245   |
| 0.2158        | 375.0 | 1500 | 1.3560          | 0.6577    | 0.7374 | 0.6952 | 0.8119   |
| 0.0184        | 500.0 | 2000 | 1.3393          | 0.6182    | 0.6869 | 0.6507 | 0.8056   |
| 0.0184        | 625.0 | 2500 | 1.3528          | 0.6087    | 0.7071 | 0.6542 | 0.8213   |
| 0.0175        | 750.0 | 3000 | 1.4282          | 0.6195    | 0.7071 | 0.6604 | 0.8182   |


### Framework versions

- Transformers 4.24.0
- Pytorch 1.13.0+cu117
- Datasets 2.7.0
- Tokenizers 0.13.2