---
license: mit
library_name: peft
tags:
- generated_from_trainer
base_model: openai-community/gpt2
datasets:
- financial_phrasebank
metrics:
- accuracy
model-index:
- name: gpt2-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. -->

# gpt2-sentiment_analysis

This model is a fine-tuned version of [openai-community/gpt2](https://huggingface.co/openai-community/gpt2) on the financial_phrasebank dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6571
- Accuracy: {'accuracy': 0.8239339752407153}

## 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: 0.0006
- train_batch_size: 4
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy                         |
|:-------------:|:------:|:----:|:---------------:|:--------------------------------:|
| No log        | 0.9981 | 257  | 0.4654          | {'accuracy': 0.8239339752407153} |
| 0.6288        | 2.0    | 515  | 0.4266          | {'accuracy': 0.8266850068775791} |
| 0.6288        | 2.9981 | 772  | 0.4558          | {'accuracy': 0.8225584594222833} |
| 0.3201        | 4.0    | 1030 | 0.4550          | {'accuracy': 0.811554332874828}  |
| 0.3201        | 4.9981 | 1287 | 0.4223          | {'accuracy': 0.8294360385144429} |
| 0.2464        | 6.0    | 1545 | 0.4637          | {'accuracy': 0.8335625859697386} |
| 0.2464        | 6.9981 | 1802 | 0.5243          | {'accuracy': 0.8184319119669876} |
| 0.1859        | 8.0    | 2060 | 0.5482          | {'accuracy': 0.8335625859697386} |
| 0.1859        | 8.9981 | 2317 | 0.6443          | {'accuracy': 0.8335625859697386} |
| 0.1381        | 9.9806 | 2570 | 0.6571          | {'accuracy': 0.8239339752407153} |


### Framework versions

- PEFT 0.11.1
- Transformers 4.41.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1