---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: fnet-base-Financial_Sentiment_Analysis
  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. -->

# fnet-base-Financial_Sentiment_Analysis

This model is a fine-tuned version of [google/fnet-base](https://huggingface.co/google/fnet-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3281
- Accuracy: 0.8117
- Weighted f1: 0.8110
- Micro f1: 0.8117
- Macro f1: 0.7472
- Weighted recall: 0.8117
- Micro recall: 0.8117
- Macro recall: 0.7394
- Weighted precision: 0.8144
- Micro precision: 0.8117
- Macro precision: 0.7588

## 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: 2e-05
- 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
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Weighted f1 | Micro f1 | Macro f1 | Weighted recall | Micro recall | Macro recall | Weighted precision | Micro precision | Macro precision |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|:--------:|:--------:|:---------------:|:------------:|:------------:|:------------------:|:---------------:|:---------------:|
| 0.6116        | 1.0   | 134  | 0.5127          | 0.6304   | 0.5606      | 0.6304   | 0.4705   | 0.6304          | 0.6304       | 0.5272       | 0.6722             | 0.6304          | 0.6103          |
| 0.4497        | 2.0   | 268  | 0.3885          | 0.7578   | 0.7490      | 0.7578   | 0.6783   | 0.7578          | 0.7578       | 0.6636       | 0.7677             | 0.7578          | 0.7196          |
| 0.3319        | 3.0   | 402  | 0.3546          | 0.7799   | 0.7784      | 0.7799   | 0.7185   | 0.7799          | 0.7799       | 0.7167       | 0.7979             | 0.7799          | 0.7440          |
| 0.2953        | 4.0   | 536  | 0.3312          | 0.8117   | 0.8105      | 0.8117   | 0.7435   | 0.8117          | 0.8117       | 0.7356       | 0.8111             | 0.8117          | 0.7532          |
| 0.2446        | 5.0   | 670  | 0.3281          | 0.8117   | 0.8110      | 0.8117   | 0.7472   | 0.8117          | 0.8117       | 0.7394       | 0.8144             | 0.8117          | 0.7588          |


### Framework versions

- Transformers 4.27.4
- Pytorch 2.0.0
- Datasets 2.11.0
- Tokenizers 0.13.3