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---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- f1
- recall
- accuracy
model-index:
- name: Bert-Thesis-NonKFold
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. -->
# Bert-Thesis-NonKFold
This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4861
- F1: 0.7464
- Recall: 0.7464
- Accuracy: 0.7464
## 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: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Recall | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:--------:|
| 1.0891 | 1.0 | 1446 | 0.9053 | 0.7222 | 0.7222 | 0.7222 |
| 0.7239 | 2.0 | 2892 | 0.8697 | 0.7397 | 0.7397 | 0.7397 |
| 0.4902 | 3.0 | 4338 | 0.8814 | 0.7491 | 0.7491 | 0.7491 |
| 0.3287 | 4.0 | 5784 | 0.9655 | 0.7512 | 0.7512 | 0.7512 |
| 0.2156 | 5.0 | 7230 | 1.0648 | 0.7450 | 0.7450 | 0.7450 |
| 0.1473 | 6.0 | 8676 | 1.1826 | 0.7446 | 0.7446 | 0.7446 |
| 0.1071 | 7.0 | 10122 | 1.2922 | 0.7465 | 0.7465 | 0.7465 |
| 0.0692 | 8.0 | 11568 | 1.4034 | 0.7483 | 0.7483 | 0.7483 |
| 0.0511 | 9.0 | 13014 | 1.4611 | 0.7478 | 0.7478 | 0.7478 |
| 0.0386 | 10.0 | 14460 | 1.4861 | 0.7464 | 0.7464 | 0.7464 |
### Framework versions
- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
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