---
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_0609_KTO_hp_screening_seeds
  results: []
---

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# llama3_false_positives_0609_KTO_hp_screening_seeds

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: 0.7798
- Eval/rewards/chosen: 0.5857
- Eval/logps/chosen: -186.9679
- Eval/rewards/rejected: 0.0902
- Eval/logps/rejected: -228.9668
- Eval/rewards/margins: 0.4955
- Eval/kl: 5.4514

## 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: 1234
- 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 |        |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.4717        | 0.96  | 12   | 0.7882          | 0.0    |
| 0.6064        | 2.0   | 25   | 0.8020          | 0.0    |
| 0.2324        | 2.96  | 37   | 0.7275          | 0.0    |
| 0.4044        | 4.0   | 50   | 0.7863          | 3.8025 |
| 0.1764        | 4.96  | 62   | 0.7797          | 5.4128 |
| 0.1937        | 5.76  | 72   | 0.7798          | 5.4514 |


### Framework versions

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