---
base_model: barc0/engineer1-heavy-barc-llama3.1-8b-ins-fft-transduction_lr1e-5_epoch3
datasets:
- barc0/transduction_augmented_test_timearc_all_evaluation_new_seperate
- barc0/transduction_rearc_dataset_400k
- barc0/transduction_heavy_100k_jsonl
library_name: peft
license: llama3.1
tags:
- alignment-handbook
- trl
- sft
- generated_from_trainer
model-index:
- name: engineer1-heavy-barc-llama3.1-8b-instruct-lora64-testtime-finetuning
  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. -->

# engineer1-heavy-barc-llama3.1-8b-instruct-lora64-testtime-finetuning

This model is a fine-tuned version of [barc0/engineer1-heavy-barc-llama3.1-8b-ins-fft-transduction_lr1e-5_epoch3](https://huggingface.co/barc0/engineer1-heavy-barc-llama3.1-8b-ins-fft-transduction_lr1e-5_epoch3) on the barc0/transduction_augmented_test_timearc_all_evaluation_new_seperate, the barc0/transduction_rearc_dataset_400k and the barc0/transduction_heavy_100k_jsonl datasets.
It achieves the following results on the evaluation set:
- Loss: 0.0333

## 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: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- total_eval_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: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.0331        | 1.0   | 1334 | 0.0359          |
| 0.028         | 2.0   | 2668 | 0.0299          |
| 0.0009        | 3.0   | 4002 | 0.0333          |


### Framework versions

- PEFT 0.12.0
- Transformers 4.45.0.dev0
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1