---
license: mit
base_model: gpt2-medium
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: gmra_model_gpt2-medium_15082023T113143
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# gmra_model_gpt2-medium_15082023T113143

This model is a fine-tuned version of [gpt2-medium](https://huggingface.co/gpt2-medium) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2694
- Accuracy: 0.9464

## 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   | 142  | 0.4750          | 0.8409   |
| No log        | 2.0   | 284  | 0.2932          | 0.9033   |
| No log        | 2.99  | 426  | 0.2850          | 0.9192   |
| 0.5761        | 4.0   | 569  | 0.2622          | 0.9279   |
| 0.5761        | 5.0   | 711  | 0.2580          | 0.9367   |
| 0.5761        | 6.0   | 853  | 0.2768          | 0.9394   |
| 0.5761        | 6.99  | 995  | 0.2640          | 0.9473   |
| 0.0682        | 8.0   | 1138 | 0.2493          | 0.9464   |
| 0.0682        | 9.0   | 1280 | 0.2739          | 0.9446   |
| 0.0682        | 9.98  | 1420 | 0.2694          | 0.9464   |


### Framework versions

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