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---
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_1010_KTO_hp_screening_seeds
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. -->
# llama3_false_positives_1010_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: 1.2449
- Eval/rewards/chosen: -0.1725
- Eval/logps/chosen: -212.3262
- Eval/rewards/rejected: -0.2031
- Eval/logps/rejected: -235.8965
- Eval/rewards/margins: 0.0307
- Eval/kl: 0.0010
## 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: 1e-05
- train_batch_size: 1
- eval_batch_size: 2
- seed: 9012
- 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 | |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 0.7665 | 0.9412 | 12 | 1.3091 | 0.0694 |
| 0.7349 | 1.9608 | 25 | 1.2881 | 0.0051 |
| 0.7221 | 2.9804 | 38 | 1.2705 | 0.0002 |
| 0.6999 | 4.0 | 51 | 1.2533 | 0.0050 |
| 0.7169 | 4.9412 | 63 | 1.2452 | 0.0 |
| 0.5263 | 5.6471 | 72 | 1.2449 | 0.0010 |
### Framework versions
- PEFT 0.11.1
- Transformers 4.44.0
- Pytorch 2.2.0
- Datasets 2.20.0
- Tokenizers 0.19.1 |