---
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
base_model: distilgpt2
model-index:
- name: distilgpt-monolinugal
  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. -->

# distilgpt-monolinugal

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: 3.4876

## 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: 0.0005
- train_batch_size: 12
- eval_batch_size: 12
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 96
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- num_epochs: 8
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 3.3098        | 0.16  | 200  | 3.5905          |
| 3.2847        | 0.32  | 400  | 3.5644          |
| 3.2612        | 0.48  | 600  | 3.5504          |
| 3.2636        | 0.64  | 800  | 3.5384          |
| 3.2481        | 0.8   | 1000 | 3.5301          |
| 3.2393        | 0.96  | 1200 | 3.5233          |
| 3.2381        | 1.12  | 1400 | 3.5184          |
| 3.2317        | 1.28  | 1600 | 3.5168          |
| 3.2244        | 1.44  | 1800 | 3.5123          |
| 3.2258        | 1.6   | 2000 | 3.5117          |
| 3.2238        | 1.76  | 2200 | 3.5058          |
| 3.2376        | 1.92  | 2400 | 3.5058          |
| 3.212         | 2.08  | 2600 | 3.5044          |
| 3.231         | 2.24  | 2800 | 3.5019          |
| 3.2044        | 2.4   | 3000 | 3.5003          |
| 3.2107        | 2.57  | 3200 | 3.5002          |
| 3.2096        | 2.73  | 3400 | 3.4996          |
| 3.215         | 2.89  | 3600 | 3.4963          |
| 3.2092        | 3.05  | 3800 | 3.4979          |
| 3.2034        | 3.21  | 4000 | 3.4964          |
| 3.1992        | 3.37  | 4200 | 3.4971          |
| 3.1975        | 3.53  | 4400 | 3.4941          |
| 3.222         | 3.69  | 4600 | 3.4932          |
| 3.2104        | 3.85  | 4800 | 3.4927          |
| 3.199         | 4.01  | 5000 | 3.4918          |
| 3.2033        | 4.17  | 5200 | 3.4927          |
| 3.201         | 4.33  | 5400 | 3.4924          |
| 3.1947        | 4.49  | 5600 | 3.4931          |
| 3.2172        | 4.65  | 5800 | 3.4907          |
| 3.201         | 4.81  | 6000 | 3.4908          |
| 3.2089        | 4.97  | 6200 | 3.4892          |
| 3.206         | 5.13  | 6400 | 3.4896          |
| 3.2074        | 5.29  | 6600 | 3.4884          |
| 3.2046        | 5.45  | 6800 | 3.4891          |
| 3.1899        | 5.61  | 7000 | 3.4888          |
| 3.196         | 5.77  | 7200 | 3.4891          |
| 3.1946        | 5.93  | 7400 | 3.4880          |
| 3.1951        | 6.09  | 7600 | 3.4887          |
| 3.1998        | 6.25  | 7800 | 3.4878          |
| 3.1775        | 6.41  | 8000 | 3.4880          |
| 3.1947        | 6.57  | 8200 | 3.4880          |
| 3.1876        | 6.73  | 8400 | 3.4876          |
| 3.1984        | 6.89  | 8600 | 3.4878          |
| 3.1927        | 7.05  | 8800 | 3.4875          |
| 3.2006        | 7.21  | 9000 | 3.4875          |
| 3.2042        | 7.37  | 9200 | 3.4875          |
| 3.1856        | 7.54  | 9400 | 3.4877          |
| 3.1952        | 7.7   | 9600 | 3.4877          |
| 3.1981        | 7.86  | 9800 | 3.4876          |


### Framework versions

- PEFT 0.7.1
- Transformers 4.36.2
- Pytorch 1.13.0+cu116
- Datasets 2.16.0
- Tokenizers 0.15.0