---
library_name: transformers
license: mit
base_model: FacebookAI/roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: f0e34afffe85e814b4e41abc80263fca
  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. -->

# f0e34afffe85e814b4e41abc80263fca

This model is a fine-tuned version of [FacebookAI/roberta-base](https://huggingface.co/FacebookAI/roberta-base) on the contemmcm/hate-speech-and-offensive-language dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3189
- Data Size: 1.0
- Epoch Runtime: 49.4083
- Accuracy: 0.9115
- F1 Macro: 0.7587

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 32
- total_eval_batch_size: 32
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: constant
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Data Size | Epoch Runtime | Accuracy | F1 Macro |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:-------------:|:--------:|:--------:|
| No log        | 0     | 0    | 1.2039          | 0         | 4.1789        | 0.0601   | 0.0378   |
| No log        | 1     | 619  | 0.6824          | 0.0078    | 4.7944        | 0.7672   | 0.2894   |
| No log        | 2     | 1238 | 0.6033          | 0.0156    | 5.1378        | 0.7672   | 0.2894   |
| 0.0148        | 3     | 1857 | 0.3472          | 0.0312    | 5.9556        | 0.8904   | 0.5871   |
| 0.0148        | 4     | 2476 | 0.2996          | 0.0625    | 7.7942        | 0.9046   | 0.6062   |
| 0.3137        | 5     | 3095 | 0.2770          | 0.125     | 10.1123       | 0.9065   | 0.7305   |
| 0.0257        | 6     | 3714 | 0.2918          | 0.25      | 15.7152       | 0.9054   | 0.6093   |
| 0.2836        | 7     | 4333 | 0.3122          | 0.5       | 27.3986       | 0.8981   | 0.7566   |
| 0.2616        | 8.0   | 4952 | 0.2436          | 1.0       | 50.3288       | 0.9164   | 0.6985   |
| 0.2095        | 9.0   | 5571 | 0.3629          | 1.0       | 49.8399       | 0.8843   | 0.6892   |
| 0.2033        | 10.0  | 6190 | 0.2972          | 1.0       | 49.5511       | 0.9150   | 0.7817   |
| 0.2164        | 11.0  | 6809 | 0.2992          | 1.0       | 50.8395       | 0.9093   | 0.7611   |
| 0.1258        | 12.0  | 7428 | 0.3189          | 1.0       | 49.4083       | 0.9115   | 0.7587   |


### Framework versions

- Transformers 4.57.0
- Pytorch 2.8.0+cu128
- Datasets 4.3.0
- Tokenizers 0.22.1