---
license: apache-2.0
language: "en"
tags:
- financial-sentiment-analysis
- sentiment-analysis
- generated_from_trainer
- financial
- stocks
- sentiment
metrics:
- f1
datasets:
- financial_phrasebank
- Kaggle Self label
- financial-classification
widget:
- text: "The USD rallied by 10% last night"
  example_title: "Bullish Sentiment"
- text: "Covid-19 cases have been increasing over the past few months"
  example_title: "Bearish Sentiment"
- text: "the USD has been trending lower"
  example_title: "Mildly Bearish Sentiment"
model-index:
- name: distilroberta-finetuned-finclass
  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-finetuned-finclass

This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on the [financial-phrasebank + Kaggle Dataset](https://huggingface.co/datasets/nickmuchi/financial-classification) dataset. The Kaggle dataset includes Covid-19 sentiment data and can be found here: [sentiment-classification-selflabel-dataset](https://www.kaggle.com/percyzheng/sentiment-classification-selflabel-dataset).
It achieves the following results on the evaluation set:
- Loss: 0.4463
- F1: 0.8835

## Model description

Model determines the financial sentiment of given text.

## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.7309        | 1.0   | 72   | 0.3671          | 0.8441 |
| 0.3757        | 2.0   | 144  | 0.3199          | 0.8709 |
| 0.3054        | 3.0   | 216  | 0.3096          | 0.8678 |
| 0.2229        | 4.0   | 288  | 0.3776          | 0.8390 |
| 0.1744        | 5.0   | 360  | 0.3678          | 0.8723 |
| 0.1436        | 6.0   | 432  | 0.3728          | 0.8758 |
| 0.1044        | 7.0   | 504  | 0.4116          | 0.8744 |
| 0.0931        | 8.0   | 576  | 0.4148          | 0.8761 |
| 0.0683        | 9.0   | 648  | 0.4423          | 0.8837 |
| 0.0611        | 10.0  | 720  | 0.4463          | 0.8835 |


### Framework versions

- Transformers 4.15.0
- Pytorch 1.10.0+cu111
- Datasets 1.18.0
- Tokenizers 0.10.3