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---
base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
library_name: peft
license: llama3.1
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: hippocrate-lora-training-2024-2
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. -->
# hippocrate-lora-training-2024-2
This model is a fine-tuned version of [meta-llama/Meta-Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B-Instruct) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7579
## 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: constant
- lr_scheduler_warmup_steps: 300
- num_epochs: 4
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:-----:|:---------------:|
| 0.817 | 0.5030 | 2000 | 0.8639 |
| 0.8933 | 1.0060 | 4000 | 0.7860 |
| 0.9076 | 1.5091 | 6000 | 0.7668 |
| 0.5954 | 2.0121 | 8000 | 0.7627 |
| 0.5311 | 2.5151 | 10000 | 0.7580 |
| 0.5863 | 3.0181 | 12000 | 0.7542 |
| 0.595 | 3.5211 | 14000 | 0.7579 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.45.0
- Pytorch 2.3.1+cu121
- Datasets 2.14.5
- Tokenizers 0.20.0 |