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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_0609_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_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: 0.5033
- Eval/rewards/chosen: 2.8767
- Eval/logps/chosen: -164.0585
- Eval/rewards/rejected: 2.4882
- Eval/logps/rejected: -204.9874
- Eval/rewards/margins: 0.3885
- Eval/kl: 24.2343
## 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 | |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.6591 | 0.96 | 12 | 0.5834 | 0.2291 |
| 0.3244 | 2.0 | 25 | 0.5716 | 15.3529 |
| 0.0459 | 2.96 | 37 | 0.5362 | 20.4863 |
| 0.07 | 4.0 | 50 | 0.5089 | 23.8717 |
| 0.0208 | 4.96 | 62 | 0.4999 | 24.2550 |
| 0.0416 | 5.76 | 72 | 0.5033 | 24.2343 |
### Framework versions
- PEFT 0.11.1
- Transformers 4.44.0
- Pytorch 2.2.0
- Datasets 2.20.0
- Tokenizers 0.19.1 |