---
base_model: ahmedrachid/FinancialBERT-Sentiment-Analysis
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: sentiment_pc_under_sampler
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# sentiment_pc_under_sampler

This model is a fine-tuned version of [ahmedrachid/FinancialBERT-Sentiment-Analysis](https://huggingface.co/ahmedrachid/FinancialBERT-Sentiment-Analysis) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5934
- Accuracy: 0.8235
- F1: 0.8236

## 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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- 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 | F1     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|
| No log        | 0.4464 | 50   | 0.5398          | 0.7797   | 0.7809 |
| No log        | 0.8929 | 100  | 0.4638          | 0.8203   | 0.8221 |
| No log        | 1.3393 | 150  | 0.4749          | 0.8183   | 0.8196 |
| No log        | 1.7857 | 200  | 0.4944          | 0.8144   | 0.8150 |
| No log        | 2.2321 | 250  | 0.5050          | 0.8157   | 0.8158 |
| No log        | 2.6786 | 300  | 0.5470          | 0.8085   | 0.8079 |
| No log        | 3.125  | 350  | 0.5299          | 0.8196   | 0.8200 |
| No log        | 3.5714 | 400  | 0.5651          | 0.8150   | 0.8146 |
| No log        | 4.0179 | 450  | 0.5684          | 0.8288   | 0.8294 |
| 0.3419        | 4.4643 | 500  | 0.5934          | 0.8235   | 0.8236 |
| 0.3419        | 4.9107 | 550  | 0.5976          | 0.8203   | 0.8208 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1