---
license: mit
base_model: gpt2-large
tags:
- generated_from_trainer
model-index:
- name: GPTL-APPS
  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. -->

# GPTL-APPS

This model is a fine-tuned version of [gpt2-large](https://huggingface.co/gpt2-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7539

## 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: 4
- eval_batch_size: 4
- 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: cosine
- lr_scheduler_warmup_steps: 100
- training_steps: 5000

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.0941        | 0.04  | 200  | 0.9988          |
| 0.8014        | 0.08  | 400  | 0.9315          |
| 0.8452        | 0.12  | 600  | 0.8909          |
| 0.9507        | 0.16  | 800  | 0.8903          |
| 0.6988        | 0.2   | 1000 | 0.8632          |
| 0.6965        | 0.24  | 1200 | 0.8553          |
| 0.7256        | 0.28  | 1400 | 0.8222          |
| 0.7109        | 0.32  | 1600 | 0.8162          |
| 0.6418        | 0.36  | 1800 | 0.8086          |
| 0.649         | 0.4   | 2000 | 0.8051          |
| 0.7378        | 0.44  | 2200 | 0.7974          |
| 0.7202        | 0.48  | 2400 | 0.7933          |
| 0.6896        | 0.52  | 2600 | 0.7817          |
| 0.5561        | 0.56  | 2800 | 0.7945          |
| 0.6497        | 0.6   | 3000 | 0.7774          |
| 0.735         | 0.64  | 3200 | 0.7758          |
| 0.5507        | 0.68  | 3400 | 0.7741          |
| 0.5615        | 0.72  | 3600 | 0.7677          |
| 0.6098        | 0.76  | 3800 | 0.7605          |
| 0.6038        | 0.8   | 4000 | 0.7653          |
| 0.5356        | 0.84  | 4200 | 0.7562          |
| 0.5699        | 0.88  | 4400 | 0.7586          |
| 0.6348        | 0.92  | 4600 | 0.7547          |
| 0.6458        | 0.96  | 4800 | 0.7539          |
| 0.6236        | 1.0   | 5000 | 0.7539          |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2