metadata

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

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 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