metadata
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: finance_news_classifier
results: []
finance_news_classifier
This model is a fine-tuned version of cardiffnlp/twitter-xlm-roberta-base-sentiment on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.1719
- Accuracy: 0.8680
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 243 | 0.4023 | 0.8412 |
| No log | 2.0 | 486 | 0.4435 | 0.8526 |
| 0.3668 | 3.0 | 729 | 0.5688 | 0.8402 |
| 0.3668 | 4.0 | 972 | 0.6626 | 0.8598 |
| 0.1479 | 5.0 | 1215 | 0.8238 | 0.8557 |
| 0.1479 | 6.0 | 1458 | 0.9073 | 0.8536 |
| 0.0654 | 7.0 | 1701 | 0.9993 | 0.8557 |
| 0.0654 | 8.0 | 1944 | 1.0495 | 0.8526 |
| 0.0368 | 9.0 | 2187 | 1.1007 | 0.8392 |
| 0.0368 | 10.0 | 2430 | 1.1122 | 0.8505 |
| 0.0212 | 11.0 | 2673 | 1.1024 | 0.8680 |
| 0.0212 | 12.0 | 2916 | 1.0697 | 0.8670 |
| 0.0148 | 13.0 | 3159 | 1.1283 | 0.8639 |
| 0.0148 | 14.0 | 3402 | 1.1176 | 0.8701 |
| 0.008 | 15.0 | 3645 | 1.1625 | 0.8660 |
| 0.008 | 16.0 | 3888 | 1.1794 | 0.8639 |
| 0.0052 | 17.0 | 4131 | 1.1701 | 0.8629 |
| 0.0052 | 18.0 | 4374 | 1.1919 | 0.8608 |
| 0.005 | 19.0 | 4617 | 1.1745 | 0.8670 |
| 0.005 | 20.0 | 4860 | 1.1719 | 0.8680 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3