---
library_name: transformers
license: mit
base_model: cardiffnlp/twitter-roberta-large-hate-latest
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: twitter-roberta-large-hate-latest-offensive-eval-kn
  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. -->

# twitter-roberta-large-hate-latest-offensive-eval-kn

This model is a fine-tuned version of [cardiffnlp/twitter-roberta-large-hate-latest](https://huggingface.co/cardiffnlp/twitter-roberta-large-hate-latest) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8543
- Accuracy: 0.7391
- Precision: 0.4215
- Recall: 0.3968
- F1: 0.4020

## 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: 1e-05
- train_batch_size: 16
- eval_batch_size: 128
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- 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     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.9082        | 0.9968 | 157  | 0.8529          | 0.7286   | 0.3746    | 0.3354 | 0.3312 |
| 0.7593        | 2.0    | 315  | 0.7818          | 0.7393   | 0.5160    | 0.3778 | 0.3767 |
| 0.7264        | 2.9968 | 472  | 0.7640          | 0.7464   | 0.4450    | 0.3812 | 0.3861 |
| 0.6998        | 4.0    | 630  | 0.7941          | 0.7464   | 0.4461    | 0.4106 | 0.4218 |
| 0.5066        | 4.9968 | 787  | 0.8636          | 0.7518   | 0.4668    | 0.4156 | 0.4276 |
| 0.5164        | 6.0    | 945  | 0.8747          | 0.7482   | 0.4391    | 0.4342 | 0.4342 |
| 0.4098        | 6.9968 | 1102 | 0.9078          | 0.7446   | 0.4366    | 0.4324 | 0.4334 |
| 0.3556        | 8.0    | 1260 | 0.9286          | 0.7393   | 0.4279    | 0.4304 | 0.4282 |
| 0.3974        | 8.9968 | 1417 | 0.9444          | 0.7446   | 0.4434    | 0.4406 | 0.4411 |
| 0.318         | 9.9683 | 1570 | 0.9597          | 0.7411   | 0.4352    | 0.4370 | 0.4352 |


### Framework versions

- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0