---
license: mit
base_model: FacebookAI/xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: roberta-finetuned-inspirational
  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-finetuned-inspirational

This model is a fine-tuned version of [FacebookAI/xlm-roberta-base](https://huggingface.co/FacebookAI/xlm-roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1617
- F1: 0.9683
- Roc Auc: 0.9622
- Accuracy: 0.9125

## 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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Roc Auc | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
| 0.312         | 1.0   | 600  | 0.2784          | 0.9053 | 0.8878  | 0.7333   |
| 0.1656        | 2.0   | 1200 | 0.1670          | 0.9468 | 0.9348  | 0.8542   |
| 0.0967        | 3.0   | 1800 | 0.1803          | 0.9585 | 0.9504  | 0.8865   |
| 0.0685        | 4.0   | 2400 | 0.1694          | 0.9639 | 0.9568  | 0.9021   |
| 0.0286        | 5.0   | 3000 | 0.1617          | 0.9683 | 0.9622  | 0.9125   |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2