metadata
library_name: transformers
base_model: ProsusAI/finbert
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: finance-sentiment-classifier
results: []
finance-sentiment-classifier
This model is a fine-tuned version of ProsusAI/finbert on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3186
- Accuracy: 0.9203
- F1: 0.9202
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: 64
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.6005 | 0.1999 | 500 | 0.5220 | 0.7970 | 0.7954 |
| 0.4518 | 0.3998 | 1000 | 0.3991 | 0.8546 | 0.8540 |
| 0.3773 | 0.5998 | 1500 | 0.3231 | 0.8813 | 0.8808 |
| 0.3375 | 0.7997 | 2000 | 0.3025 | 0.8878 | 0.8881 |
| 0.2982 | 0.9996 | 2500 | 0.2735 | 0.8977 | 0.8971 |
| 0.2057 | 1.1995 | 3000 | 0.3028 | 0.9035 | 0.9026 |
| 0.2001 | 1.3994 | 3500 | 0.2624 | 0.9123 | 0.9119 |
| 0.2034 | 1.5994 | 4000 | 0.2450 | 0.9171 | 0.9170 |
| 0.1631 | 1.7993 | 4500 | 0.2547 | 0.9180 | 0.9179 |
| 0.1691 | 1.9992 | 5000 | 0.2379 | 0.9189 | 0.9189 |
| 0.1077 | 2.1991 | 5500 | 0.2982 | 0.9190 | 0.9186 |
| 0.1288 | 2.3990 | 6000 | 0.2772 | 0.9201 | 0.9199 |
| 0.1114 | 2.5990 | 6500 | 0.2847 | 0.9220 | 0.9220 |
| 0.1128 | 2.7989 | 7000 | 0.2879 | 0.9234 | 0.9233 |
| 0.0969 | 2.9988 | 7500 | 0.2920 | 0.9236 | 0.9234 |
Framework versions
- Transformers 4.57.6
- Pytorch 2.9.1+cu128
- Datasets 4.5.0
- Tokenizers 0.22.2