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---
license: apache-2.0
base_model: distilgpt2
tags:
- generated_from_trainer
model-index:
- name: distilgpt2-alpaca-instruction-fine-tuning-qlora
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-alpaca-instruction-fine-tuning-qlora
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: 2.2461
## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 1000
- num_epochs: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.9811 | 0.11 | 1000 | 2.4141 |
| 2.5312 | 0.22 | 2000 | 2.3164 |
| 2.4908 | 0.33 | 3000 | 2.2871 |
| 2.4785 | 0.44 | 4000 | 2.2754 |
| 2.4518 | 0.55 | 5000 | 2.2832 |
| 2.4277 | 0.66 | 6000 | 2.2578 |
| 2.4352 | 0.77 | 7000 | 2.25 |
| 2.4171 | 0.88 | 8000 | 2.2480 |
| 2.4138 | 0.99 | 9000 | 2.2461 |
### Framework versions
- Transformers 4.33.3
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
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