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---
library_name: transformers
license: apache-2.0
base_model: bert-base-uncased
tags:
- text-classification
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: results
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. -->
# results
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: 0.1922
- Accuracy: 0.9640
- Precision: 0.926
- Recall: 0.7928
- F1: 0.8542
## 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: 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: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.1639 | 1.0 | 1097 | 0.1940 | 0.9389 | 0.8762 | 0.6301 | 0.7331 |
| 0.1069 | 2.0 | 2194 | 0.1561 | 0.9608 | 0.9478 | 0.7466 | 0.8352 |
| 0.0897 | 3.0 | 3291 | 0.1922 | 0.9640 | 0.926 | 0.7928 | 0.8542 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Tokenizers 0.19.1
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