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---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
datasets:
- financial_phrasebank
metrics:
- accuracy
model-index:
- name: distilbert-finance
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: 0.7427685950413223
---
<!-- 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. -->
# distilbert-finance
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the financial_phrasebank dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9820
- Accuracy: 0.7428
## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.905 | 0.33 | 20 | 1.5902 | 0.4205 |
| 0.66 | 0.66 | 40 | 1.6678 | 0.4184 |
| 0.5429 | 0.98 | 60 | 1.6024 | 0.3915 |
| 0.4804 | 1.31 | 80 | 1.5001 | 0.4236 |
| 0.3914 | 1.64 | 100 | 1.4990 | 0.4246 |
| 0.3817 | 1.97 | 120 | 1.3082 | 0.4225 |
| 0.2829 | 2.3 | 140 | 1.0931 | 0.4566 |
| 0.2737 | 2.62 | 160 | 0.9830 | 0.5579 |
| 0.2958 | 2.95 | 180 | 0.8748 | 0.6281 |
| 0.1963 | 3.28 | 200 | 0.7356 | 0.7335 |
| 0.1861 | 3.61 | 220 | 1.0993 | 0.5599 |
| 0.2025 | 3.93 | 240 | 0.7504 | 0.75 |
| 0.1326 | 4.26 | 260 | 0.8450 | 0.7438 |
| 0.1491 | 4.59 | 280 | 0.7221 | 0.7593 |
| 0.1303 | 4.92 | 300 | 0.9738 | 0.6756 |
| 0.109 | 5.25 | 320 | 0.7593 | 0.7634 |
| 0.0994 | 5.57 | 340 | 1.1073 | 0.6632 |
| 0.0969 | 5.9 | 360 | 0.8082 | 0.7479 |
| 0.0697 | 6.23 | 380 | 0.9121 | 0.7242 |
| 0.0635 | 6.56 | 400 | 0.8706 | 0.7490 |
| 0.0637 | 6.89 | 420 | 1.0041 | 0.7221 |
| 0.0561 | 7.21 | 440 | 1.0379 | 0.7035 |
| 0.0577 | 7.54 | 460 | 1.0113 | 0.7180 |
| 0.0612 | 7.87 | 480 | 0.9029 | 0.75 |
| 0.0505 | 8.2 | 500 | 0.9523 | 0.7428 |
| 0.0493 | 8.52 | 520 | 0.9854 | 0.7304 |
| 0.0271 | 8.85 | 540 | 1.0400 | 0.7252 |
| 0.0271 | 9.18 | 560 | 1.0337 | 0.7314 |
| 0.0397 | 9.51 | 580 | 1.0058 | 0.7366 |
| 0.0441 | 9.84 | 600 | 0.9820 | 0.7428 |
### Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3
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