---
library_name: transformers
base_model: cardiffnlp/twitter-roberta-base-hate
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: test_dir_model3
  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. -->

# test_dir_model3

This model is a fine-tuned version of [cardiffnlp/twitter-roberta-base-hate](https://huggingface.co/cardiffnlp/twitter-roberta-base-hate) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2679
- Accuracy: 0.8783
- F1: 0.6997
- Precision: 0.8118
- Recall: 0.6915

## 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: 64
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- num_epochs: 10
- label_smoothing_factor: 0.1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| No log        | 1.0   | 35   | 1.1935          | 0.7304   | 0.3920 | 0.3732    | 0.4740 |
| No log        | 2.0   | 70   | 1.2142          | 0.8348   | 0.6136 | 0.6065    | 0.6625 |
| 0.9237        | 3.0   | 105  | 1.3719          | 0.8783   | 0.7167 | 0.7802    | 0.7244 |
| 0.9237        | 4.0   | 140  | 1.5517          | 0.8696   | 0.7135 | 0.7685    | 0.7367 |
| 0.9237        | 5.0   | 175  | 1.9028          | 0.8870   | 0.7282 | 0.7874    | 0.7423 |
| 0.3387        | 6.0   | 210  | 2.0006          | 0.8696   | 0.6333 | 0.775     | 0.6708 |
| 0.3387        | 7.0   | 245  | 2.1684          | 0.8783   | 0.6997 | 0.8118    | 0.6915 |
| 0.3387        | 8.0   | 280  | 2.1672          | 0.8696   | 0.6958 | 0.7972    | 0.7038 |
| 0.119         | 9.0   | 315  | 2.2526          | 0.8783   | 0.6997 | 0.8118    | 0.6915 |
| 0.119         | 10.0  | 350  | 2.2679          | 0.8783   | 0.6997 | 0.8118    | 0.6915 |


### Framework versions

- Transformers 4.57.3
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1