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license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
- recall
- precision
model-index:
- name: pulf-classifier_roberta_final
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_roberta_final
This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0165
- Accuracy: 0.9954
- F1-score: 0.9909
- Recall: 0.9917
- Precision: 0.9902
## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:--------:|:------:|:---------:|
| 0.0248 | 1.0 | 10746 | 0.0204 | 0.9937 | 0.9875 | 0.9859 | 0.9891 |
| 0.0228 | 2.0 | 21492 | 0.0152 | 0.9963 | 0.9926 | 0.9906 | 0.9946 |
| 0.0201 | 3.0 | 32238 | 0.0165 | 0.9954 | 0.9909 | 0.9917 | 0.9902 |
### Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3
|