---
license: mit
base_model: Aravindan/gpt2out
tags:
- generated_from_trainer
model-index:
- name: gpt2coder-8epochs
  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. -->

# gpt2coder-8epochs

This model is a fine-tuned version of [Aravindan/gpt2out](https://huggingface.co/Aravindan/gpt2out) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6964

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20

### Training results

| Training Loss | Epoch   | Step | Validation Loss |
|:-------------:|:-------:|:----:|:---------------:|
| No log        | 0.9962  | 132  | 1.5428          |
| No log        | 2.0     | 265  | 1.4204          |
| No log        | 2.9962  | 397  | 1.2888          |
| 1.5725        | 4.0     | 530  | 1.1900          |
| 1.5725        | 4.9962  | 662  | 1.1045          |
| 1.5725        | 6.0     | 795  | 1.0314          |
| 1.5725        | 6.9962  | 927  | 0.9723          |
| 1.217         | 8.0     | 1060 | 0.9139          |
| 1.217         | 8.9962  | 1192 | 0.8689          |
| 1.217         | 10.0    | 1325 | 0.8274          |
| 1.217         | 10.9962 | 1457 | 0.7910          |
| 1.0164        | 12.0    | 1590 | 0.7555          |
| 1.0164        | 12.9962 | 1722 | 0.7266          |
| 1.0164        | 14.0    | 1855 | 0.7014          |
| 1.0164        | 14.9962 | 1987 | 0.6777          |
| 0.8885        | 16.0    | 2120 | 0.6597          |
| 0.8885        | 16.9962 | 2252 | 0.6440          |
| 0.8885        | 18.0    | 2385 | 0.6327          |
| 0.8106        | 18.9962 | 2517 | 0.6239          |
| 0.8106        | 19.9962 | 2640 | 0.6964          |


### Framework versions

- Transformers 4.41.1
- Pytorch 2.1.2
- Datasets 2.19.1
- Tokenizers 0.19.1