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---
license: mit
base_model: FacebookAI/roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: uniBERT.RoBERTa.2
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. -->
# uniBERT.RoBERTa.2
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: 1.5630
- Accuracy: (0.5576407506702413,)
- F1: (0.5567150966762268,)
- Precision: (0.5821362469913879,)
- Recall: 0.5576
## 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: 64
- 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 | Accuracy | F1 | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:----------------------:|:----------------------:|:----------------------:|:------:|
| 3.2109 | 1.0 | 187 | 2.8161 | (0.14075067024128687,) | (0.11441602156126289,) | (0.14931859559553662,) | 0.1408 |
| 2.379 | 2.0 | 374 | 2.1989 | (0.29624664879356566,) | (0.29511135501125035,) | (0.46510470134694354,) | 0.2962 |
| 1.8982 | 3.0 | 561 | 1.8944 | (0.39812332439678283,) | (0.3899880572417641,) | (0.5315801863934072,) | 0.3981 |
| 1.5421 | 4.0 | 748 | 1.7216 | (0.435656836461126,) | (0.43699437984272427,) | (0.5225927530578255,) | 0.4357 |
| 1.2096 | 5.0 | 935 | 1.6234 | (0.4906166219839142,) | (0.4898871795571693,) | (0.5614942106807528,) | 0.4906 |
| 1.0077 | 6.0 | 1122 | 1.5807 | (0.5201072386058981,) | (0.5180183790949172,) | (0.5564502396694377,) | 0.5201 |
| 0.9205 | 7.0 | 1309 | 1.5927 | (0.5308310991957105,) | (0.5275104307804458,) | (0.5702694562019299,) | 0.5308 |
| 0.7537 | 8.0 | 1496 | 1.5717 | (0.532171581769437,) | (0.5297487624770745,) | (0.5623053308004577,) | 0.5322 |
| 0.6635 | 9.0 | 1683 | 1.5720 | (0.5495978552278821,) | (0.5497874364324945,) | (0.579798743930685,) | 0.5496 |
| 0.6479 | 10.0 | 1870 | 1.5630 | (0.5576407506702413,) | (0.5567150966762268,) | (0.5821362469913879,) | 0.5576 |
### Framework versions
- Transformers 4.39.3
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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