metadata
base_model: yiyanghkust/finbert-tone
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: tradepulse-finbert-sentiment
results: []
tradepulse-finbert-sentiment
This model is a fine-tuned version of yiyanghkust/finbert-tone on the None dataset. It achieves the following results on the evaluation set:
- Loss: 3.3717
- Accuracy: 0.5
- Precision: 0.7222
- Recall: 0.5
- F1: 0.5
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 5
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 3 | 6.2763 | 0.3333 | 0.2083 | 0.3333 | 0.2333 |
| No log | 2.0 | 6 | 3.9344 | 0.5 | 0.7222 | 0.5 | 0.5 |
| No log | 3.0 | 9 | 3.3717 | 0.5 | 0.7222 | 0.5 | 0.5 |
Framework versions
- Transformers 4.41.0
- Pytorch 2.7.1+cpu
- Datasets 2.19.1
- Tokenizers 0.19.1