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---
base_model: readerbench/RoBERT-base
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
model-index:
- name: ro-offense-01
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. -->
# ro-offense-01
This model is a fine-tuned version of [readerbench/RoBERT-base](https://huggingface.co/readerbench/RoBERT-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8411
- Accuracy: 0.8232
- Precision: 0.8235
- Recall: 0.8210
- F1 Macro: 0.8207
- F1 Micro: 0.8232
- F1 Weighted: 0.8210
## 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: 4e-05
- train_batch_size: 64
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.2
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 Macro | F1 Micro | F1 Weighted |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:--------:|:--------:|:-----------:|
| No log | 1.0 | 125 | 0.7789 | 0.7037 | 0.6825 | 0.7000 | 0.6873 | 0.7037 | 0.7132 |
| No log | 2.0 | 250 | 0.5170 | 0.8006 | 0.8066 | 0.8016 | 0.7986 | 0.8006 | 0.7971 |
| No log | 3.0 | 375 | 0.5139 | 0.8096 | 0.8168 | 0.8237 | 0.8120 | 0.8096 | 0.8047 |
| 0.6074 | 4.0 | 500 | 0.6180 | 0.8247 | 0.8251 | 0.8187 | 0.8210 | 0.8247 | 0.8233 |
| 0.6074 | 5.0 | 625 | 0.7311 | 0.8096 | 0.8071 | 0.8085 | 0.8064 | 0.8096 | 0.8071 |
| 0.6074 | 6.0 | 750 | 0.8365 | 0.8101 | 0.8117 | 0.8191 | 0.8105 | 0.8101 | 0.8051 |
| 0.6074 | 7.0 | 875 | 0.8411 | 0.8232 | 0.8235 | 0.8210 | 0.8207 | 0.8232 | 0.8210 |
### Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.3
- Tokenizers 0.13.3
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