metadata
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-base
tags:
- generated_from_trainer
datasets:
- financial_phrasebank
metrics:
- accuracy
model-index:
- name: ModernFinBERT
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: financial_phrasebank
type: financial_phrasebank
config: sentences_50agree
split: train
args: sentences_50agree
metrics:
- name: Accuracy
type: accuracy
value: 0.8670103092783505
ModernFinBERT
This model is a fine-tuned version of answerdotai/ModernBERT-base on the financial_phrasebank dataset. It achieves the following results on the evaluation set:
- Loss: 0.6635
- Accuracy: 0.8670
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: 8e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-06 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.5348 | 1.0 | 122 | 0.4122 | 0.8278 |
| 0.2684 | 2.0 | 244 | 0.3491 | 0.8546 |
| 0.1303 | 3.0 | 366 | 0.4818 | 0.8536 |
| 0.0569 | 4.0 | 488 | 0.6635 | 0.8670 |
| 0.0298 | 5.0 | 610 | 0.7434 | 0.8629 |
| 0.0166 | 6.0 | 732 | 0.7884 | 0.8660 |
Framework versions
- Transformers 4.48.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0