---
license: mit
base_model: FacebookAI/roberta-base
tags:
- generated_from_trainer
model-index:
- name: roberta-base
  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. -->

# roberta-base

This model is a fine-tuned version of [FacebookAI/roberta-base](https://huggingface.co/FacebookAI/roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6584
- Icm: 0.0568
- Icmnorm: 0.5288
- Fmeasure: 0.6851

## 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: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Icm     | Icmnorm | Fmeasure |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:--------:|
| No log        | 1.0   | 193  | 0.6695          | -0.1296 | 0.4342  | 0.6006   |
| No log        | 2.0   | 386  | 0.6774          | -0.1417 | 0.4281  | 0.5798   |
| 0.5681        | 3.0   | 579  | 0.6584          | 0.0568  | 0.5288  | 0.6851   |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2