---
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