---
license: llama3.1
base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: Llams_3.1_8B_instruct_behaviour_cloning_extra_things_updated_grouped
  results: []
library_name: peft
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Llams_3.1_8B_instruct_behaviour_cloning_extra_things_updated_grouped

This model is a fine-tuned version of [meta-llama/Meta-Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B-Instruct) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1928
- Model Preparation Time: 0.0065

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure


The following `bitsandbytes` quantization config was used during training:
- quant_method: bitsandbytes
- _load_in_8bit: False
- _load_in_4bit: True
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: None
- llm_int8_enable_fp32_cpu_offload: False
- llm_int8_has_fp16_weight: False
- bnb_4bit_quant_type: nf4
- bnb_4bit_use_double_quant: True
- bnb_4bit_compute_dtype: bfloat16
- bnb_4bit_quant_storage: uint8
- load_in_4bit: True
- load_in_8bit: False
### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Model Preparation Time |
|:-------------:|:------:|:----:|:---------------:|:----------------------:|
| 0.0929        | 0.9996 | 1236 | 0.1423          | 0.0065                 |
| 0.0689        | 2.0    | 2473 | 0.1724          | 0.0065                 |
| 0.0588        | 2.9988 | 3708 | 0.1928          | 0.0065                 |


### Framework versions

- PEFT 0.4.0
- Transformers 4.44.0
- Pytorch 2.3.1+cu121
- Datasets 2.13.0
- Tokenizers 0.19.1