---
license: mit
base_model: gpt2
tags:
- generated_from_trainer
model-index:
- name: distilgpt2-CLM-DSM-NoOerlap
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# distilgpt2-CLM-DSM-NoOerlap

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: 2.4500

## 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   | 84   | 2.6146          |
| No log        | 2.0   | 168  | 2.5488          |
| No log        | 3.0   | 252  | 2.5136          |
| No log        | 4.0   | 336  | 2.4924          |
| No log        | 5.0   | 420  | 2.4777          |
| 2.6089        | 6.0   | 504  | 2.4665          |
| 2.6089        | 7.0   | 588  | 2.4599          |
| 2.6089        | 8.0   | 672  | 2.4540          |
| 2.6089        | 9.0   | 756  | 2.4509          |
| 2.6089        | 10.0  | 840  | 2.4500          |


### Framework versions

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