---
library_name: transformers
license: mit
base_model: gpt2
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: sentimental-gpt
  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. -->

# sentimental-gpt

This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5305
- Accuracy: 0.7985

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- 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: 500
- num_epochs: 3

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.7515        | 0.2910 | 500  | 0.6684          | 0.7187   |
| 0.6015        | 0.5821 | 1000 | 0.5922          | 0.7609   |
| 0.5758        | 0.8731 | 1500 | 0.5355          | 0.7804   |
| 0.5301        | 1.1641 | 2000 | 0.5441          | 0.7801   |
| 0.4545        | 1.4552 | 2500 | 0.5318          | 0.7917   |
| 0.5103        | 1.7462 | 3000 | 0.5479          | 0.7796   |
| 0.4495        | 2.0373 | 3500 | 0.5212          | 0.7906   |
| 0.4506        | 2.3283 | 4000 | 0.5282          | 0.7963   |
| 0.4271        | 2.6193 | 4500 | 0.5305          | 0.7985   |
| 0.44          | 2.9104 | 5000 | 0.5335          | 0.7971   |


### Framework versions

- Transformers 4.49.0
- Pytorch 2.0.0+cu118
- Datasets 3.3.1
- Tokenizers 0.21.0