metadata
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: fin_sentiment
results: []
fin_sentiment
This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.0101
- Accuracy: 0.8624
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: 8
- eval_batch_size: 8
- 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 |
|---|---|---|---|---|
| 0.527 | 1.0 | 515 | 0.4239 | 0.8514 |
| 0.3018 | 2.0 | 1030 | 0.4353 | 0.8707 |
| 0.1509 | 3.0 | 1545 | 0.7413 | 0.8446 |
| 0.1069 | 4.0 | 2060 | 0.7788 | 0.8611 |
| 0.0585 | 5.0 | 2575 | 0.8656 | 0.8624 |
| 0.0397 | 6.0 | 3090 | 0.8394 | 0.8666 |
| 0.0233 | 7.0 | 3605 | 0.9554 | 0.8624 |
| 0.0171 | 8.0 | 4120 | 0.9459 | 0.8583 |
| 0.0128 | 9.0 | 4635 | 0.9991 | 0.8597 |
| 0.0033 | 10.0 | 5150 | 1.0101 | 0.8624 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2