metadata
tags:
- generated_from_trainer
datasets:
- financial_phrasebank
metrics:
- accuracy
- f1
model-index:
- name: financial-sentiment-analysis
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: financial_phrasebank
type: financial_phrasebank
args: sentences_allagree
metrics:
- name: Accuracy
type: accuracy
value: 0.9924242424242424
- name: F1
type: f1
value: 0.9924242424242424
financial-sentiment-analysis
This model is a fine-tuned version of ahmedrachid/FinancialBERT on the financial_phrasebank dataset. It achieves the following results on the evaluation set:
- Loss: 0.0395
- Accuracy: 0.9924
- F1: 0.9924
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: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
Framework versions
- Transformers 4.19.1
- Pytorch 1.11.0+cu113
- Datasets 2.2.1
- Tokenizers 0.12.1