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library_name: transformers
license: mit
base_model: FacebookAI/roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: roberta-base-kennedy2020constructing
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. -->
# roberta-base-kennedy2020constructing
This model is a fine-tuned version of [FacebookAI/roberta-base](https://huggingface.co/FacebookAI/roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2110
- Accuracy: 0.9738
- Roc Auc: 0.9915
- Precision: 0.9680
- Recall: 0.9592
- F1: 0.9636
## 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: 96
- eval_batch_size: 128
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Roc Auc | Precision | Recall | F1 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:-------:|:---------:|:------:|:------:|
| 0.2481 | 1.0 | 1144 | 0.2172 | 0.9001 | 0.9676 | 0.9266 | 0.7861 | 0.8506 |
| 0.1822 | 2.0 | 2288 | 0.1604 | 0.9380 | 0.9836 | 0.9252 | 0.9017 | 0.9133 |
| 0.1085 | 3.0 | 3432 | 0.1343 | 0.9575 | 0.9893 | 0.9627 | 0.9180 | 0.9398 |
| 0.0674 | 4.0 | 4576 | 0.1225 | 0.9649 | 0.9918 | 0.9477 | 0.9558 | 0.9517 |
| 0.0502 | 5.0 | 5720 | 0.1455 | 0.9688 | 0.9919 | 0.9561 | 0.9576 | 0.9569 |
| 0.0365 | 6.0 | 6864 | 0.1370 | 0.9698 | 0.9921 | 0.9676 | 0.9481 | 0.9578 |
| 0.0258 | 7.0 | 8008 | 0.1719 | 0.9706 | 0.9925 | 0.9615 | 0.9570 | 0.9592 |
| 0.0184 | 8.0 | 9152 | 0.1737 | 0.9731 | 0.9922 | 0.9686 | 0.9567 | 0.9626 |
| 0.0141 | 9.0 | 10296 | 0.2051 | 0.9734 | 0.9916 | 0.9673 | 0.9588 | 0.9630 |
| 0.01 | 10.0 | 11440 | 0.2110 | 0.9738 | 0.9915 | 0.9680 | 0.9592 | 0.9636 |
### Framework versions
- Transformers 4.49.0
- Pytorch 2.6.0+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0
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