---
base_model: meta-llama/Meta-Llama-3-8B-Instruct
library_name: peft
license: llama3
tags:
- trl
- kto
- generated_from_trainer
model-index:
- name: llama3_false_positives_1609_KTO_optimised_model
  results: []
---

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# llama3_false_positives_1609_KTO_optimised_model

This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5894
- Eval/rewards/chosen: 2.7219
- Eval/logps/chosen: -170.9184
- Eval/rewards/rejected: 2.5085
- Eval/logps/rejected: -185.9287
- Eval/rewards/margins: 0.2134
- Eval/kl: 25.1066

## 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: 0.0001
- train_batch_size: 1
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 6.0

### Training results

| Training Loss | Epoch | Step | Validation Loss |         |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.4841        | 0.96  | 12   | 0.6000          | 13.4542 |
| 0.1395        | 2.0   | 25   | 0.5894          | 25.1066 |


### Framework versions

- PEFT 0.11.1
- Transformers 4.44.0
- Pytorch 2.2.0
- Datasets 2.20.0
- Tokenizers 0.19.1