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---
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
|