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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: 0.7285
- Accuracy: 0.8132
- Precision: 0.8131
- Recall: 0.8173
- F1 Macro: 0.8123
- F1 Micro: 0.8132
- F1 Weighted: 0.8094
## 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: 64
- eval_batch_size: 128
- 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 | Precision | Recall | F1 Macro | F1 Micro | F1 Weighted |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:--------:|:--------:|:-----------:|
| No log | 1.0 | 125 | 0.6284 | 0.7675 | 0.7662 | 0.7721 | 0.7681 | 0.7675 | 0.7654 |
| No log | 2.0 | 250 | 0.5576 | 0.7820 | 0.7826 | 0.7799 | 0.7796 | 0.7820 | 0.7803 |
| No log | 3.0 | 375 | 0.5405 | 0.8001 | 0.8122 | 0.8077 | 0.8026 | 0.8001 | 0.7943 |
| 0.5338 | 4.0 | 500 | 0.5853 | 0.8172 | 0.8140 | 0.8120 | 0.8124 | 0.8172 | 0.8161 |
| 0.5338 | 5.0 | 625 | 0.6476 | 0.8157 | 0.8143 | 0.8098 | 0.8118 | 0.8157 | 0.8148 |
| 0.5338 | 6.0 | 750 | 0.6607 | 0.8122 | 0.8137 | 0.8173 | 0.8120 | 0.8122 | 0.8082 |
| 0.5338 | 7.0 | 875 | 0.7285 | 0.8132 | 0.8131 | 0.8173 | 0.8123 | 0.8132 | 0.8094 |
### Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.3
- Tokenizers 0.13.3
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