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---
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: finbert-finetuned-FG-SINGLE_SENTENCE-NEWS
results: []
---
<!-- 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. -->
# finbert-finetuned-FG-SINGLE_SENTENCE-NEWS
This model is a fine-tuned version of [ProsusAI/finbert](https://huggingface.co/ProsusAI/finbert) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 4.0147
- Accuracy: 0.5361
- F1: 0.5346
## 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: 6e-05
- train_batch_size: 32
- eval_batch_size: 32
- 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 | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log | 1.0 | 198 | 1.0442 | 0.4616 | 0.4093 |
| No log | 2.0 | 396 | 1.0938 | 0.4875 | 0.4455 |
| 0.9778 | 3.0 | 594 | 1.1884 | 0.5247 | 0.5161 |
| 0.9778 | 4.0 | 792 | 1.3903 | 0.5338 | 0.5290 |
| 0.9778 | 5.0 | 990 | 1.5180 | 0.5452 | 0.5430 |
| 0.3904 | 6.0 | 1188 | 1.8556 | 0.5270 | 0.5273 |
| 0.3904 | 7.0 | 1386 | 2.1461 | 0.5376 | 0.5386 |
| 0.142 | 8.0 | 1584 | 2.4582 | 0.5529 | 0.5489 |
| 0.142 | 9.0 | 1782 | 2.6054 | 0.5255 | 0.5247 |
| 0.142 | 10.0 | 1980 | 2.7953 | 0.5544 | 0.5483 |
| 0.0797 | 11.0 | 2178 | 3.0892 | 0.5308 | 0.5315 |
| 0.0797 | 12.0 | 2376 | 3.3025 | 0.5384 | 0.5315 |
| 0.0415 | 13.0 | 2574 | 3.3124 | 0.5308 | 0.5249 |
| 0.0415 | 14.0 | 2772 | 3.6247 | 0.5331 | 0.5322 |
| 0.0415 | 15.0 | 2970 | 3.6592 | 0.5224 | 0.5252 |
| 0.024 | 16.0 | 3168 | 3.8275 | 0.5308 | 0.5290 |
| 0.024 | 17.0 | 3366 | 3.8818 | 0.5308 | 0.5295 |
| 0.009 | 18.0 | 3564 | 3.9417 | 0.5407 | 0.5375 |
| 0.009 | 19.0 | 3762 | 4.0033 | 0.5361 | 0.5339 |
| 0.009 | 20.0 | 3960 | 4.0147 | 0.5361 | 0.5346 |
### Framework versions
- Transformers 4.16.2
- Pytorch 1.9.1
- Datasets 1.18.4
- Tokenizers 0.11.6
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