metadata
library_name: transformers
base_model: ProsusAI/finbert
tags:
- finBERT
- sequence-classification
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: finBERT-phraseBank
results: []
finBERT-phraseBank
This model is a fine-tuned version of ProsusAI/finbert on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4035
- Accuracy: 0.8557
- F1 Macro: 0.8299
- Precision Macro: 0.8246
- Recall Macro: 0.8359
- F1 Weighted: 0.8556
- Precision Weighted: 0.8559
- Recall Weighted: 0.8557
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 OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | Precision Macro | Recall Macro | F1 Weighted | Precision Weighted | Recall Weighted |
|---|---|---|---|---|---|---|---|---|---|---|
| 0.5357 | 1.0 | 243 | 0.4582 | 0.8258 | 0.7967 | 0.8014 | 0.7968 | 0.8235 | 0.8256 | 0.8258 |
| 0.4427 | 2.0 | 486 | 0.4090 | 0.8371 | 0.8098 | 0.8037 | 0.8186 | 0.8366 | 0.8375 | 0.8371 |
| 0.2711 | 3.0 | 729 | 0.4035 | 0.8557 | 0.8299 | 0.8246 | 0.8359 | 0.8556 | 0.8559 | 0.8557 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1