LABEL_0 LABEL_1 LABEL_2
---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- financial_phrasebank
metrics:
- accuracy
- f1
model-index:
- name: finetuning-finetuned-financial-phrasebank-75
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: financial_phrasebank
      type: financial_phrasebank
      args: sentences_75agree
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9217391304347826
    - name: F1
      type: f1
      value: 0.9222750587883506
---

<!-- 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. -->

# finetuning-finetuned-financial-phrasebank-75

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: 0.5900
- Accuracy: 0.9217
- F1: 0.9223

## 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: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 80

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.6566        | 1.0   | 22   | 0.4940          | 0.8435   | 0.8448 |
| 0.4136        | 2.0   | 44   | 0.2829          | 0.9188   | 0.9195 |
| 0.2286        | 3.0   | 66   | 0.2404          | 0.9159   | 0.9159 |
| 0.1389        | 4.0   | 88   | 0.2527          | 0.9275   | 0.9280 |
| 0.0921        | 5.0   | 110  | 0.2555          | 0.9333   | 0.9336 |
| 0.0634        | 6.0   | 132  | 0.2987          | 0.9159   | 0.9168 |
| 0.0441        | 7.0   | 154  | 0.3032          | 0.9188   | 0.9198 |
| 0.0354        | 8.0   | 176  | 0.3167          | 0.9246   | 0.9253 |
| 0.0184        | 9.0   | 198  | 0.3296          | 0.9217   | 0.9220 |
| 0.0182        | 10.0  | 220  | 0.3284          | 0.9304   | 0.9305 |
| 0.0119        | 11.0  | 242  | 0.3513          | 0.9217   | 0.9223 |
| 0.008         | 12.0  | 264  | 0.4218          | 0.9217   | 0.9225 |
| 0.0068        | 13.0  | 286  | 0.4115          | 0.9188   | 0.9197 |
| 0.0077        | 14.0  | 308  | 0.4209          | 0.9159   | 0.9169 |
| 0.0037        | 15.0  | 330  | 0.4120          | 0.9217   | 0.9220 |
| 0.0026        | 16.0  | 352  | 0.4134          | 0.9159   | 0.9161 |
| 0.0026        | 17.0  | 374  | 0.4230          | 0.9217   | 0.9221 |
| 0.0025        | 18.0  | 396  | 0.4335          | 0.9275   | 0.9278 |
| 0.0016        | 19.0  | 418  | 0.4538          | 0.9188   | 0.9187 |
| 0.0022        | 20.0  | 440  | 0.4518          | 0.9188   | 0.9192 |
| 0.0011        | 21.0  | 462  | 0.4653          | 0.9159   | 0.9167 |
| 0.0011        | 22.0  | 484  | 0.4713          | 0.9159   | 0.9167 |
| 0.0008        | 23.0  | 506  | 0.4585          | 0.9217   | 0.9223 |
| 0.0007        | 24.0  | 528  | 0.4525          | 0.9275   | 0.9278 |
| 0.0007        | 25.0  | 550  | 0.4582          | 0.9304   | 0.9307 |
| 0.0009        | 26.0  | 572  | 0.4689          | 0.9275   | 0.9279 |
| 0.0006        | 27.0  | 594  | 0.4783          | 0.9275   | 0.9279 |
| 0.0019        | 28.0  | 616  | 0.4784          | 0.9275   | 0.9279 |
| 0.0013        | 29.0  | 638  | 0.4884          | 0.9246   | 0.9253 |
| 0.0006        | 30.0  | 660  | 0.5065          | 0.9217   | 0.9217 |
| 0.0036        | 31.0  | 682  | 0.4800          | 0.9246   | 0.9253 |
| 0.0007        | 32.0  | 704  | 0.4643          | 0.9304   | 0.9305 |
| 0.0009        | 33.0  | 726  | 0.4633          | 0.9275   | 0.9279 |
| 0.0004        | 34.0  | 748  | 0.4787          | 0.9275   | 0.9279 |
| 0.0004        | 35.0  | 770  | 0.4912          | 0.9217   | 0.9224 |
| 0.0004        | 36.0  | 792  | 0.4693          | 0.9246   | 0.9247 |
| 0.0004        | 37.0  | 814  | 0.4962          | 0.9246   | 0.9251 |
| 0.0004        | 38.0  | 836  | 0.5034          | 0.9246   | 0.9251 |
| 0.0003        | 39.0  | 858  | 0.5096          | 0.9188   | 0.9197 |
| 0.0003        | 40.0  | 880  | 0.5065          | 0.9246   | 0.9252 |
| 0.0003        | 41.0  | 902  | 0.4894          | 0.9246   | 0.9244 |
| 0.0005        | 42.0  | 924  | 0.5419          | 0.9159   | 0.9168 |
| 0.0016        | 43.0  | 946  | 0.5230          | 0.9217   | 0.9225 |
| 0.0003        | 44.0  | 968  | 0.5272          | 0.9159   | 0.9169 |
| 0.0003        | 45.0  | 990  | 0.4794          | 0.9275   | 0.9275 |
| 0.0003        | 46.0  | 1012 | 0.5131          | 0.9217   | 0.9223 |
| 0.0005        | 47.0  | 1034 | 0.5256          | 0.9246   | 0.9242 |
| 0.0004        | 48.0  | 1056 | 0.5571          | 0.9159   | 0.9168 |
| 0.0003        | 49.0  | 1078 | 0.5412          | 0.9246   | 0.9252 |
| 0.0005        | 50.0  | 1100 | 0.5465          | 0.9217   | 0.9225 |
| 0.0013        | 51.0  | 1122 | 0.5324          | 0.9333   | 0.9337 |
| 0.0002        | 52.0  | 1144 | 0.5284          | 0.9333   | 0.9337 |
| 0.0002        | 53.0  | 1166 | 0.5301          | 0.9304   | 0.9308 |
| 0.0002        | 54.0  | 1188 | 0.5317          | 0.9275   | 0.9280 |
| 0.0002        | 55.0  | 1210 | 0.5476          | 0.9246   | 0.9252 |
| 0.001         | 56.0  | 1232 | 0.5277          | 0.9333   | 0.9335 |
| 0.0002        | 57.0  | 1254 | 0.5387          | 0.9246   | 0.9251 |
| 0.0005        | 58.0  | 1276 | 0.5505          | 0.9246   | 0.9253 |
| 0.0006        | 59.0  | 1298 | 0.5400          | 0.9304   | 0.9306 |
| 0.0022        | 60.0  | 1320 | 0.5788          | 0.9159   | 0.9169 |
| 0.0002        | 61.0  | 1342 | 0.5504          | 0.9275   | 0.9277 |
| 0.0003        | 62.0  | 1364 | 0.5686          | 0.9275   | 0.9275 |
| 0.0002        | 63.0  | 1386 | 0.5653          | 0.9159   | 0.9165 |
| 0.0002        | 64.0  | 1408 | 0.5700          | 0.9188   | 0.9194 |
| 0.0002        | 65.0  | 1430 | 0.5705          | 0.9188   | 0.9194 |
| 0.0002        | 66.0  | 1452 | 0.5687          | 0.9159   | 0.9165 |
| 0.0003        | 67.0  | 1474 | 0.5971          | 0.9159   | 0.9168 |
| 0.0002        | 68.0  | 1496 | 0.5979          | 0.9188   | 0.9196 |
| 0.0009        | 69.0  | 1518 | 0.5905          | 0.9217   | 0.9223 |
| 0.0002        | 70.0  | 1540 | 0.5845          | 0.9188   | 0.9192 |
| 0.0003        | 71.0  | 1562 | 0.5942          | 0.9217   | 0.9223 |
| 0.0002        | 72.0  | 1584 | 0.5948          | 0.9217   | 0.9223 |
| 0.0002        | 73.0  | 1606 | 0.5943          | 0.9217   | 0.9223 |
| 0.0006        | 74.0  | 1628 | 0.5931          | 0.9217   | 0.9223 |
| 0.0002        | 75.0  | 1650 | 0.5927          | 0.9217   | 0.9223 |
| 0.0002        | 76.0  | 1672 | 0.5940          | 0.9217   | 0.9223 |
| 0.0002        | 77.0  | 1694 | 0.5937          | 0.9217   | 0.9223 |
| 0.0002        | 78.0  | 1716 | 0.5911          | 0.9217   | 0.9223 |
| 0.0006        | 79.0  | 1738 | 0.5900          | 0.9217   | 0.9223 |
| 0.0002        | 80.0  | 1760 | 0.5900          | 0.9217   | 0.9223 |


### Framework versions

- Transformers 4.17.0
- Pytorch 1.10.1+cpu
- Datasets 2.0.0
- Tokenizers 0.11.6
