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license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- recall
- precision
model-index:
- name: pulf-classifier
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. -->
# pulf-classifier
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0233
- Accuracy: 0.9943
- F1-score: 0.9887
- Recall: 0.9910
- Precision: 0.9863
## 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: 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 | F1-score | Recall | Precision |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:--------:|:------:|:---------:|
| 0.0243 | 1.0 | 8772 | 0.0228 | 0.9930 | 0.9861 | 0.9877 | 0.9846 |
| 0.0183 | 2.0 | 17544 | 0.0243 | 0.9937 | 0.9875 | 0.9927 | 0.9825 |
| 0.0124 | 3.0 | 26316 | 0.0233 | 0.9943 | 0.9887 | 0.9910 | 0.9863 |
### Framework versions
- Transformers 4.27.4
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3
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