---
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
model-index:
- name: RoBERTa-perigon-news
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# RoBERTa-perigon-news

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: 0.9548

## Model description

The model was pre-trained for a MLM taskusing over 200K financial news articles obtaind from Perigon https://www.goperigon.com/.  

## 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: 8.7e-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: 15

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 1.4872        | 1.0   | 5480  | 1.3355          |
| 1.3571        | 2.0   | 10960 | 1.2488          |
| 1.3078        | 3.0   | 16440 | 1.2144          |
| 1.2425        | 4.0   | 21920 | 1.1634          |
| 1.2035        | 5.0   | 27400 | 1.1309          |
| 1.157         | 6.0   | 32880 | 1.0941          |
| 1.1268        | 7.0   | 38360 | 1.0696          |
| 1.098         | 8.0   | 43840 | 1.0466          |
| 1.0681        | 9.0   | 49320 | 1.0297          |
| 1.0356        | 10.0  | 54800 | 1.0168          |
| 1.0194        | 11.0  | 60280 | 1.0011          |
| 0.9941        | 12.0  | 65760 | 0.9843          |
| 0.981         | 13.0  | 71240 | 0.9716          |
| 0.9634        | 14.0  | 76720 | 0.9600          |
| 0.9511        | 15.0  | 82200 | 0.9546          |


### Framework versions

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