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---
base_model: facebook/roberta-hate-speech-dynabench-r4-target
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: facebook-hate-speech-fine-tuned
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. -->
# facebook-hate-speech-fine-tuned
This model is a fine-tuned version of [facebook/roberta-hate-speech-dynabench-r4-target](https://huggingface.co/facebook/roberta-hate-speech-dynabench-r4-target) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1943
- Accuracy: 0.9636
- Precision Macro: 0.8675
- Recall Macro: 0.8731
- F1 Macro: 0.8703
- Precision Micro: 0.9636
- Recall Micro: 0.9636
- F1 Micro: 0.9636
## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision Macro | Recall Macro | F1 Macro | Precision Micro | Recall Micro | F1 Micro |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------------:|:------------:|:--------:|:---------------:|:------------:|:--------:|
| 0.2628 | 1.0 | 199 | 0.1203 | 0.9585 | 0.8840 | 0.7939 | 0.8318 | 0.9585 | 0.9585 | 0.9585 |
| 0.071 | 2.0 | 398 | 0.1640 | 0.9673 | 0.9144 | 0.8369 | 0.8709 | 0.9673 | 0.9673 | 0.9673 |
| 0.1483 | 3.0 | 597 | 0.1943 | 0.9636 | 0.8675 | 0.8731 | 0.8703 | 0.9636 | 0.9636 | 0.9636 |
### Framework versions
- Transformers 4.42.4
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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