---
license: mit
base_model: gpt2
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: gmra_model_gpt2_14082023T103028
  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. -->

# gmra_model_gpt2_14082023T103028

This model is a fine-tuned version of [gpt2](https://huggingface.co./gpt2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2685
- Accuracy: 0.9192

## 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: 4
- total_train_batch_size: 64
- 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        | 1.0   | 71   | 0.6906          | 0.7742   |
| No log        | 1.99  | 142  | 0.4773          | 0.8286   |
| No log        | 2.99  | 213  | 0.3916          | 0.8708   |
| No log        | 4.0   | 285  | 0.3393          | 0.8849   |
| No log        | 5.0   | 356  | 0.3144          | 0.9007   |
| No log        | 5.99  | 427  | 0.2959          | 0.9112   |
| No log        | 6.99  | 498  | 0.2825          | 0.9165   |
| 0.538         | 8.0   | 570  | 0.2803          | 0.9069   |
| 0.538         | 9.0   | 641  | 0.2612          | 0.9192   |
| 0.538         | 9.96  | 710  | 0.2685          | 0.9192   |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3