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

# cudaTest

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: 0.6334
- Compute Metrics: :
- Accuracy: 0.676
- Balanced Accuracy: 0.4893
- F1 Score: 0.8058
- Recall: 0.9655
- Precision: 0.6914

## 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: 32
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 256
- 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 | Compute Metrics | Accuracy | Balanced Accuracy | F1 Score | Recall | Precision |
|:-------------:|:-----:|:----:|:---------------:|:---------------:|:--------:|:-----------------:|:--------:|:------:|:---------:|
| No log        | 1.0   | 2    | 0.6369          | :               | 0.688    | 0.5017            | 0.8134   | 0.9770 | 0.6967    |
| No log        | 2.0   | 4    | 0.6302          | :               | 0.684    | 0.5043            | 0.8092   | 0.9626 | 0.6979    |
| No log        | 3.0   | 6    | 0.6313          | :               | 0.69     | 0.4975            | 0.8161   | 0.9885 | 0.6949    |
| No log        | 4.0   | 8    | 0.6338          | :               | 0.668    | 0.4854            | 0.7995   | 0.9511 | 0.6896    |
| 0.6818        | 5.0   | 10   | 0.6334          | :               | 0.676    | 0.4893            | 0.8058   | 0.9655 | 0.6914    |


### Framework versions

- Transformers 4.26.0
- Pytorch 1.13.1+cu117
- Datasets 2.9.0
- Tokenizers 0.13.2