---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: distilroberta-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. -->

# distilroberta-base

This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6935
- Precision: 0.7556
- Recall: 0.7556
- F1: 0.7556
- Accuracy: 0.7556

## 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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.2481        | 1.0   | 2355 | 1.5506          | 0.7409    | 0.7409 | 0.7409 | 0.7409   |
| 0.3473        | 2.0   | 4710 | 1.5572          | 0.7428    | 0.7428 | 0.7428 | 0.7428   |
| 0.2614        | 3.0   | 7065 | 1.6423          | 0.7539    | 0.7539 | 0.7539 | 0.7539   |
| 0.1337        | 4.0   | 9420 | 1.6935          | 0.7556    | 0.7556 | 0.7556 | 0.7556   |


### Framework versions

- Transformers 4.28.1
- Pytorch 1.13.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3