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---
library_name: transformers
license: mit
base_model: FacebookAI/roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: roberta-large-csb
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-large-csb
This model is a fine-tuned version of [FacebookAI/roberta-large](https://huggingface.co/FacebookAI/roberta-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2625
- Accuracy: 0.8857
- F1: 0.8860
## 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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- 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
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.3718 | 1.0 | 228 | 0.2774 | 0.8747 | 0.8748 |
| 0.3126 | 2.0 | 456 | 0.2625 | 0.8857 | 0.8860 |
| 0.2053 | 3.0 | 684 | 0.3058 | 0.8791 | 0.8787 |
| 0.1797 | 4.0 | 912 | 0.4676 | 0.8615 | 0.8601 |
| 0.1087 | 5.0 | 1140 | 0.8824 | 0.8330 | 0.8288 |
| 0.0827 | 6.0 | 1368 | 0.9341 | 0.8637 | 0.8616 |
| 0.0336 | 7.0 | 1596 | 0.9355 | 0.8571 | 0.8552 |
| 0.0077 | 8.0 | 1824 | 0.9166 | 0.8725 | 0.8720 |
| 0.0011 | 9.0 | 2052 | 0.9783 | 0.8747 | 0.8740 |
| 0.0001 | 10.0 | 2280 | 1.0445 | 0.8703 | 0.8692 |
### Framework versions
- Transformers 4.57.3
- Pytorch 2.2.1
- Datasets 4.4.1
- Tokenizers 0.22.1
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