---
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: 0.7386363636363636
---

<!-- 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: 0.9962
- Accuracy: 0.7386

## 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: cosine
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.904         | 0.33  | 20   | 1.5959          | 0.4205   |
| 0.6562        | 0.66  | 40   | 1.6665          | 0.4143   |
| 0.539         | 0.98  | 60   | 1.6067          | 0.3936   |
| 0.4759        | 1.31  | 80   | 1.5079          | 0.4236   |
| 0.3882        | 1.64  | 100  | 1.4719          | 0.4298   |
| 0.3782        | 1.97  | 120  | 1.2392          | 0.4267   |
| 0.2729        | 2.3   | 140  | 1.0114          | 0.4928   |
| 0.2607        | 2.62  | 160  | 0.9514          | 0.5930   |
| 0.2889        | 2.95  | 180  | 0.8661          | 0.6477   |
| 0.181         | 3.28  | 200  | 0.7093          | 0.7417   |
| 0.1742        | 3.61  | 220  | 1.1042          | 0.5764   |
| 0.1904        | 3.93  | 240  | 0.7439          | 0.7510   |
| 0.1186        | 4.26  | 260  | 0.8587          | 0.7469   |
| 0.137         | 4.59  | 280  | 0.7408          | 0.7603   |
| 0.1166        | 4.92  | 300  | 1.0107          | 0.6705   |
| 0.0938        | 5.25  | 320  | 0.7883          | 0.7624   |
| 0.0881        | 5.57  | 340  | 1.0339          | 0.7056   |
| 0.0812        | 5.9   | 360  | 0.8409          | 0.7490   |
| 0.0586        | 6.23  | 380  | 0.9146          | 0.7345   |
| 0.0572        | 6.56  | 400  | 0.9000          | 0.7366   |
| 0.0527        | 6.89  | 420  | 0.9782          | 0.7335   |
| 0.045         | 7.21  | 440  | 1.0102          | 0.7262   |
| 0.0471        | 7.54  | 460  | 1.0322          | 0.7324   |
| 0.0508        | 7.87  | 480  | 0.9381          | 0.7448   |
| 0.039         | 8.2   | 500  | 0.9489          | 0.7459   |
| 0.0419        | 8.52  | 520  | 0.9779          | 0.7469   |
| 0.0256        | 8.85  | 540  | 0.9834          | 0.7407   |
| 0.0264        | 9.18  | 560  | 0.9963          | 0.7376   |
| 0.0378        | 9.51  | 580  | 0.9981          | 0.7376   |
| 0.0421        | 9.84  | 600  | 0.9962          | 0.7386   |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3