metadata
library_name: transformers
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
datasets:
- financial_phrasebank
metrics:
- f1
model-index:
- name: FIN_BERT_sentiment
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: financial_phrasebank
type: financial_phrasebank
config: sentences_66agree
split: train
args: sentences_66agree
metrics:
- name: F1
type: f1
value: 0.8890693407692588
FIN_BERT_sentiment
This model is a fine-tuned version of bert-base-uncased on the financial_phrasebank dataset. It achieves the following results on the evaluation set:
- Loss: 0.4905
- F1: 0.8891
- Acc: 0.8886
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Acc |
|---|---|---|---|---|---|
| 0.5295 | 1.0 | 211 | 0.3757 | 0.8731 | 0.8720 |
| 0.2174 | 2.0 | 422 | 0.3117 | 0.8911 | 0.8910 |
| 0.1129 | 3.0 | 633 | 0.4066 | 0.8886 | 0.8874 |
| 0.0459 | 4.0 | 844 | 0.4923 | 0.8896 | 0.8886 |
| 0.0275 | 5.0 | 1055 | 0.4905 | 0.8891 | 0.8886 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1
- Datasets 3.1.0
- Tokenizers 0.20.3