---
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: temp_model_output_dir
  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. -->

# temp_model_output_dir

This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7204
- Precision: 0.8552
- Recall: 0.8448
- F1: 0.8399
- Accuracy: 0.8448

## 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: 8.8e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.2
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 1.209         | 1.0   | 756  | 0.7528          | 0.8238    | 0.8130 | 0.8013 | 0.8130   |
| 0.7337        | 2.0   | 1512 | 0.7899          | 0.8209    | 0.8031 | 0.7952 | 0.8031   |
| 0.644         | 3.0   | 2268 | 0.7417          | 0.8394    | 0.8299 | 0.8238 | 0.8299   |
| 0.4777        | 4.0   | 3024 | 0.7204          | 0.8552    | 0.8448 | 0.8399 | 0.8448   |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.15.0