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---
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: roberta-finetuned-sem_eval-rest14-english
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-finetuned-sem_eval-rest14-english
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: 0.0813
- F1: 0.5700
- Roc Auc: 0.8939
- Accuracy: 0.7312
- Hamming Loss: 0.0225
## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy | Hamming Loss |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|:------------:|
| No log | 1.0 | 381 | 0.1438 | 0.1120 | 0.6888 | 0.33 | 0.044 |
| 0.2014 | 2.0 | 762 | 0.1059 | 0.3044 | 0.7981 | 0.5587 | 0.0317 |
| 0.1093 | 3.0 | 1143 | 0.0914 | 0.3720 | 0.8325 | 0.6275 | 0.0278 |
| 0.0809 | 4.0 | 1524 | 0.0823 | 0.4290 | 0.8656 | 0.6913 | 0.0244 |
| 0.0809 | 5.0 | 1905 | 0.0862 | 0.4307 | 0.8680 | 0.6963 | 0.0251 |
| 0.06 | 6.0 | 2286 | 0.0811 | 0.4674 | 0.8714 | 0.7013 | 0.0239 |
| 0.0466 | 7.0 | 2667 | 0.0842 | 0.5041 | 0.8714 | 0.7 | 0.0248 |
| 0.0365 | 8.0 | 3048 | 0.0821 | 0.5351 | 0.8846 | 0.7137 | 0.0238 |
| 0.0365 | 9.0 | 3429 | 0.0815 | 0.5375 | 0.8857 | 0.7212 | 0.0234 |
| 0.0299 | 10.0 | 3810 | 0.0812 | 0.5551 | 0.8918 | 0.7312 | 0.0222 |
| 0.0236 | 11.0 | 4191 | 0.0815 | 0.5537 | 0.8940 | 0.7338 | 0.0222 |
| 0.0195 | 12.0 | 4572 | 0.0813 | 0.5700 | 0.8939 | 0.7312 | 0.0225 |
| 0.0195 | 13.0 | 4953 | 0.0829 | 0.5641 | 0.8955 | 0.7362 | 0.022 |
| 0.018 | 14.0 | 5334 | 0.0829 | 0.5662 | 0.8946 | 0.7338 | 0.0221 |
| 0.0157 | 15.0 | 5715 | 0.0824 | 0.5698 | 0.8980 | 0.7362 | 0.0217 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
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