---
library_name: transformers
license: apache-2.0
base_model: distilgpt2
tags:
- generated_from_trainer
model-index:
- name: distilgpt2-finetuned-wellness
  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-finetuned-wellness

This model is a fine-tuned version of [distilgpt2](https://huggingface.co/distilgpt2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7698

## 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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss |
|:-------------:|:-------:|:----:|:---------------:|
| 3.4055        | 0.9927  | 102  | 2.8632          |
| 2.6839        | 1.9951  | 205  | 2.3235          |
| 2.3467        | 2.9976  | 308  | 2.1428          |
| 2.1832        | 4.0     | 411  | 2.0383          |
| 2.0576        | 4.9927  | 513  | 1.9659          |
| 1.9634        | 5.9951  | 616  | 1.9195          |
| 1.8834        | 6.9976  | 719  | 1.8783          |
| 1.8251        | 8.0     | 822  | 1.8546          |
| 1.7861        | 8.9927  | 924  | 1.8331          |
| 1.7299        | 9.9951  | 1027 | 1.8186          |
| 1.6952        | 10.9976 | 1130 | 1.8070          |
| 1.673         | 12.0    | 1233 | 1.7945          |
| 1.6387        | 12.9927 | 1335 | 1.7904          |
| 1.6138        | 13.9951 | 1438 | 1.7845          |
| 1.6028        | 14.9976 | 1541 | 1.7793          |
| 1.5778        | 16.0    | 1644 | 1.7761          |
| 1.5668        | 16.9927 | 1746 | 1.7727          |
| 1.5534        | 17.9951 | 1849 | 1.7719          |
| 1.5557        | 18.9976 | 1952 | 1.7711          |
| 1.5438        | 19.8540 | 2040 | 1.7698          |


### Framework versions

- Transformers 4.45.1
- Pytorch 2.4.1+cu124
- Datasets 3.0.1
- Tokenizers 0.20.0