---
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
model-index:
- name: roberta-base-pretrained-perigon200k
  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-pretrained-perigon200k

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: 0.9840

## 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: 8.5e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.19
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 1.4678        | 1.0   | 5480  | 1.3180          |
| 1.3713        | 2.0   | 10960 | 1.2695          |
| 1.2673        | 3.0   | 16440 | 1.1842          |
| 1.211         | 4.0   | 21920 | 1.1350          |
| 1.1646        | 5.0   | 27400 | 1.0997          |
| 1.1181        | 6.0   | 32880 | 1.0630          |
| 1.0859        | 7.0   | 38360 | 1.0344          |
| 1.0561        | 8.0   | 43840 | 1.0126          |
| 1.0244        | 9.0   | 49320 | 0.9944          |
| 1.0006        | 10.0  | 54800 | 0.9881          |


### Framework versions

- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3