---
license: mit
base_model: gpt2
tags:
- generated_from_trainer
model-index:
- name: distilgpt2-CLM-DSM
  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-CLM-DSM

This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.4049

## 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: 8
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log        | 1.0   | 91   | 2.6265          |
| No log        | 2.0   | 182  | 2.5381          |
| No log        | 3.0   | 273  | 2.4948          |
| No log        | 4.0   | 364  | 2.4634          |
| No log        | 5.0   | 455  | 2.4436          |
| 2.6065        | 6.0   | 546  | 2.4276          |
| 2.6065        | 7.0   | 637  | 2.4176          |
| 2.6065        | 8.0   | 728  | 2.4103          |
| 2.6065        | 9.0   | 819  | 2.4061          |
| 2.6065        | 10.0  | 910  | 2.4049          |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.2.1
- Datasets 2.19.2
- Tokenizers 0.19.1