---
library_name: transformers
license: apache-2.0
base_model: samchain/econo-sentence-v2
tags:
- generated_from_trainer
- finance
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: EconoSentiment
  results: []
datasets:
- FinanceMTEB/financial_phrasebank
language:
- en
pipeline_tag: text-classification
---

<!-- 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. -->

# EconoSentiment

This model is a fine-tuned version of [samchain/econo-sentence-v2](https://huggingface.co/samchain/econo-sentence-v2) on the Financial Phrase Bank dataset from FinanceMTEB.
The full model is trained using a small learning rate isntead of freezing the encoder. Hence, you should not use the encoder of this model for a task other than sentiment analysis.

It achieves the following results on the evaluation set:
- Loss: 0.1293
- Accuracy: 0.962
- F1: 0.9619
- Precision: 0.9619
- Recall: 0.962

## Model description

The base model is a sentence-transformers model built from [EconoBert](https://huggingface.co/samchain/EconoBert).

## Intended uses & limitations

This model is trained to provide a useful tool for sentiment analysis in finance.

## Training and evaluation data

The dataset is directly downloaded from the huggingface repo of the FinanceMTEB. The preprocessing consisted of tokenizing to a fixed sequence length of 512 tokens.

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 3e-05
- train_batch_size: 8
- eval_batch_size: 16
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.5992        | 1.0   | 158  | 0.4854          | 0.805    | 0.7692 | 0.8108    | 0.805  |
| 0.0985        | 2.0   | 316  | 0.1293          | 0.962    | 0.9619 | 0.9619    | 0.962  |


### Framework versions

- Transformers 4.50.0
- Pytorch 2.1.0+cu118
- Datasets 3.4.1
- Tokenizers 0.21.1