metadata
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: []
distilroberta-finetuned-finclass
This model is a fine-tuned version of distilroberta-base on the financial-phrasebank + Kaggle Dataset. The Kaggle dataset includes Covid-19 sentiment data and can be found here: 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. Given the unbalanced distribution of the class labels, the weights were adjusted to pay attention to the less sampled labels which should increase overall performance.
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