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---
base_model: prosusai/finbert
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: finbert-fomc
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-fomc
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: 0.8286
- Accuracy: 0.6154
## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| No log | 0.0083 | 1 | 1.7351 | 0.4049 |
| 1.7127 | 0.2149 | 26 | 1.4334 | 0.4777 |
| 1.3539 | 0.4215 | 51 | 1.0763 | 0.5547 |
| 1.0501 | 0.6281 | 76 | 0.9471 | 0.5547 |
| 0.9614 | 0.8347 | 101 | 0.9471 | 0.5628 |
| 0.988 | 1.0 | 121 | 0.9030 | 0.5709 |
| 0.988 | 1.0413 | 126 | 0.8999 | 0.5547 |
| 0.8862 | 1.2479 | 151 | 0.9215 | 0.5628 |
| 0.8506 | 1.4545 | 176 | 0.8740 | 0.5506 |
| 0.8825 | 1.6612 | 201 | 0.8604 | 0.6235 |
| 0.8366 | 1.8678 | 226 | 0.8063 | 0.6194 |
| 0.7666 | 2.0 | 242 | 0.8286 | 0.6154 |
| 0.7039 | 2.0744 | 251 | 0.8652 | 0.6073 |
| 0.5698 | 2.2810 | 276 | 1.0371 | 0.5911 |
| 0.7683 | 2.4876 | 301 | 0.9662 | 0.5951 |
| 0.528 | 2.6942 | 326 | 0.8984 | 0.6275 |
| 0.6282 | 2.9008 | 351 | 0.9095 | 0.6154 |
| 0.5638 | 3.0 | 363 | 0.8730 | 0.6761 |
| 0.5208 | 3.1074 | 376 | 0.9042 | 0.6599 |
| 0.4426 | 3.3140 | 401 | 1.0531 | 0.6235 |
| 0.5795 | 3.5207 | 426 | 1.0305 | 0.6559 |
| 0.363 | 3.7273 | 451 | 0.9831 | 0.6559 |
| 0.4584 | 3.9339 | 476 | 0.9950 | 0.6437 |
| 0.3794 | 4.0 | 484 | 1.0740 | 0.6154 |
| 0.2579 | 4.1405 | 501 | 1.1667 | 0.6356 |
| 0.1803 | 4.3471 | 526 | 1.0366 | 0.6883 |
| 0.1824 | 4.5537 | 551 | 1.2625 | 0.6599 |
| 0.2647 | 4.7603 | 576 | 1.2183 | 0.6761 |
| 0.205 | 4.9669 | 601 | 1.1944 | 0.6721 |
| 0.205 | 5.0 | 605 | 1.1959 | 0.6721 |
### Framework versions
- Transformers 4.40.2
- Pytorch 1.12.0
- Datasets 2.19.1
- Tokenizers 0.19.1
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