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---
base_model: ProsusAI/finbert
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: finbert_Synonym-wordnet
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_Synonym-wordnet
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: 0.2734
- Accuracy: 0.9236
- F1: 0.9232
- Precision: 0.9236
- Recall: 0.9236
## 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: 0.0001
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 25
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.7941 | 1.0 | 91 | 0.7038 | 0.7051 | 0.6964 | 0.7046 | 0.7051 |
| 0.3785 | 2.0 | 182 | 0.2841 | 0.8939 | 0.8940 | 0.8942 | 0.8939 |
| 0.213 | 3.0 | 273 | 0.2432 | 0.9080 | 0.9082 | 0.9106 | 0.9080 |
| 0.1268 | 4.0 | 364 | 0.3080 | 0.8924 | 0.8927 | 0.8956 | 0.8924 |
| 0.0851 | 5.0 | 455 | 0.2941 | 0.9173 | 0.9166 | 0.9183 | 0.9173 |
| 0.0797 | 6.0 | 546 | 0.2734 | 0.9236 | 0.9232 | 0.9236 | 0.9236 |
| 0.0651 | 7.0 | 637 | 0.3518 | 0.8970 | 0.8975 | 0.9029 | 0.8970 |
| 0.0779 | 8.0 | 728 | 0.4189 | 0.8939 | 0.8942 | 0.9016 | 0.8939 |
| 0.0923 | 9.0 | 819 | 0.3289 | 0.9126 | 0.9131 | 0.9152 | 0.9126 |
| 0.087 | 10.0 | 910 | 0.3797 | 0.9048 | 0.9047 | 0.9075 | 0.9048 |
| 0.0527 | 11.0 | 1001 | 0.3492 | 0.9048 | 0.9050 | 0.9058 | 0.9048 |
### Framework versions
- Transformers 4.37.0
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.1
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