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---
base_model: NousResearch/Meta-Llama-3.1-8B-Instruct
datasets:
- generator
library_name: peft
license: llama3.1
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: llama381binstruct_summarize_short
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. -->
# llama381binstruct_summarize_short
This model is a fine-tuned version of [NousResearch/Meta-Llama-3.1-8B-Instruct](https://huggingface.co/NousResearch/Meta-Llama-3.1-8B-Instruct) on the generator dataset.
It achieves the following results on the evaluation set:
- Loss: 2.5418
## 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: 0.0002
- train_batch_size: 1
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 30
- training_steps: 500
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-------:|:----:|:---------------:|
| 1.7346 | 1.1905 | 25 | 1.5509 |
| 0.876 | 2.3810 | 50 | 1.6489 |
| 0.3296 | 3.5714 | 75 | 1.7988 |
| 0.1572 | 4.7619 | 100 | 2.0011 |
| 0.0918 | 5.9524 | 125 | 2.1469 |
| 0.0518 | 7.1429 | 150 | 2.1057 |
| 0.0343 | 8.3333 | 175 | 2.1788 |
| 0.0133 | 9.5238 | 200 | 2.2228 |
| 0.01 | 10.7143 | 225 | 2.2292 |
| 0.0112 | 11.9048 | 250 | 2.2735 |
| 0.0073 | 13.0952 | 275 | 2.3250 |
| 0.0037 | 14.2857 | 300 | 2.3380 |
| 0.0028 | 15.4762 | 325 | 2.4173 |
| 0.0019 | 16.6667 | 350 | 2.4736 |
| 0.0019 | 17.8571 | 375 | 2.5015 |
| 0.0023 | 19.0476 | 400 | 2.5184 |
| 0.002 | 20.2381 | 425 | 2.5288 |
| 0.0015 | 21.4286 | 450 | 2.5356 |
| 0.0016 | 22.6190 | 475 | 2.5401 |
| 0.0013 | 23.8095 | 500 | 2.5418 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.44.2
- Pytorch 2.3.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1 |