---
library_name: transformers
license: apache-2.0
base_model: distilgpt2
tags:
- generated_from_trainer
model-index:
- name: distilgpt2-instruct
  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. -->

# distilgpt2-instruct

This model is a fine-tuned version of [distilgpt2](https://huggingface.co/distilgpt2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 3.1097

## 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: 3e-05
- train_batch_size: 8
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 1
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 3.6082        | 0.0757 | 200  | 3.4527          |
| 3.4472        | 0.1514 | 400  | 3.3252          |
| 3.3842        | 0.2271 | 600  | 3.2697          |
| 3.3915        | 0.3027 | 800  | 3.2255          |
| 3.3209        | 0.3784 | 1000 | 3.1980          |
| 3.3036        | 0.4541 | 1200 | 3.1748          |
| 3.2422        | 0.5298 | 1400 | 3.1566          |
| 3.2840        | 0.6055 | 1600 | 3.1415          |
| 3.2755        | 0.6812 | 1800 | 3.1303          |
| 3.2236        | 0.7569 | 2000 | 3.1217          |
| 3.1934        | 0.8325 | 2200 | 3.1143          |
| 3.2567        | 0.9082 | 2400 | 3.1107          |
| 3.2337        | 0.9839 | 2600 | 3.1097          |


### Framework versions

- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.8.5
- Tokenizers 0.22.2