|
--- |
|
license: apache-2.0 |
|
base_model: bert-base-uncased |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- financial_phrasebank |
|
metrics: |
|
- f1 |
|
- accuracy |
|
model-index: |
|
- name: phrasebank-sentiment-analysis |
|
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: F1 |
|
type: f1 |
|
value: 0.8369540630005199 |
|
- name: Accuracy |
|
type: accuracy |
|
value: 0.8514442916093535 |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
# phrasebank-sentiment-analysis |
|
|
|
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the financial_phrasebank dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.5738 |
|
- F1: 0.8370 |
|
- Accuracy: 0.8514 |
|
|
|
## 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: 5e-05 |
|
- train_batch_size: 32 |
|
- eval_batch_size: 8 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 4 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | F1 | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:------:|:--------:| |
|
| 0.6737 | 0.94 | 100 | 0.4361 | 0.7936 | 0.8287 | |
|
| 0.3148 | 1.89 | 200 | 0.3941 | 0.8269 | 0.8494 | |
|
| 0.1572 | 2.83 | 300 | 0.5384 | 0.8289 | 0.8494 | |
|
| 0.0615 | 3.77 | 400 | 0.5738 | 0.8370 | 0.8514 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.34.1 |
|
- Pytorch 2.1.0+cu118 |
|
- Datasets 2.14.6 |
|
- Tokenizers 0.14.1 |
|
|
