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library_name: transformers
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: roberta-base_LOGIC_LRTC
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_LOGIC_LRTC
This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9419
- Accuracy: 0.6933
- Macro Precision: 0.6604
- Macro F1: 0.6503
## 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: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 12
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Macro Precision | Macro F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------------:|:--------:|
| No log | 1.0 | 116 | 1.5639 | 0.41 | 0.4728 | 0.3904 |
| No log | 2.0 | 232 | 1.1501 | 0.5833 | 0.5591 | 0.5659 |
| No log | 3.0 | 348 | 1.1315 | 0.64 | 0.6182 | 0.6220 |
| No log | 4.0 | 464 | 1.2345 | 0.67 | 0.6471 | 0.6237 |
| 0.9897 | 5.0 | 580 | 1.3952 | 0.62 | 0.5912 | 0.5960 |
| 0.9897 | 6.0 | 696 | 1.5032 | 0.68 | 0.6370 | 0.6407 |
| 0.9897 | 7.0 | 812 | 1.6859 | 0.6833 | 0.6437 | 0.6478 |
| 0.9897 | 8.0 | 928 | 1.9130 | 0.69 | 0.6638 | 0.6393 |
| 0.0959 | 9.0 | 1044 | 1.9246 | 0.68 | 0.6526 | 0.6459 |
| 0.0959 | 10.0 | 1160 | 1.8800 | 0.6867 | 0.6378 | 0.6392 |
| 0.0959 | 11.0 | 1276 | 1.9436 | 0.69 | 0.6623 | 0.6519 |
| 0.0959 | 12.0 | 1392 | 1.9419 | 0.6933 | 0.6604 | 0.6503 |
### Framework versions
- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2
|