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---
base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
library_name: peft
license: llama3.1
tags:
- generated_from_trainer
model-index:
- name: models/loras2/40a0412a-574f-442e-8a35-32dd97008a01
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. -->
[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
<details><summary>See axolotl config</summary>
axolotl version: `0.4.1`
```yaml
adapter: lora
base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
base_model_config: meta-llama/Meta-Llama-3.1-8B-Instruct
bf16: true
dataset_processes: 8
datasets:
- path: /tmp/train.jsonl
type:
field_instruction: input
field_output: output
field_system: system
format: '{instruction}'
no_input_format: '{instruction}'
system_prompt: ''
flash_attention: true
fp16: false
fsdp: []
gradient_accumulation_steps: 4
gradient_checkpointing: true
group_by_length: false
is_llama_derived_model: true
learning_rate: 0.0002
logging_steps: 1
lora_alpha: 16
lora_dropout: 0.05
lora_r: 8
lora_target_linear: true
lora_target_modules:
- gate_proj
- down_proj
- up_proj
- q_proj
- v_proj
- k_proj
- o_proj
lr_scheduler: cosine
micro_batch_size: 2
model_type: LlamaForCausalLM
num_epochs: 1
optimizer: adamw_bnb_8bit
output_dir: /models/loras2/40a0412a-574f-442e-8a35-32dd97008a01
pad_to_sequence_len: true
sample_packing: true
save_safetensors: true
save_strategy: 'no'
sequence_len: 8192
special_tokens:
eos_token: <|eot_id|>
pad_token: <|end_of_text|>
strict: true
tf32: false
tokenizer_type: AutoTokenizer
train_on_inputs: false
val_set_size: 0
wandb_project: OP Method
wandb_run_id: auth-12-1-24-gpt4o-relabeled-llama31
warmup_steps: 10
weight_decay: 0
```
</details><br>
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/openpipe-team/OP%20Method/runs/auth-12-1-24-gpt4o-relabeled-llama31)
# models/loras2/40a0412a-574f-442e-8a35-32dd97008a01
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.
## 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
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- num_epochs: 1
### Training results
### Framework versions
- PEFT 0.11.1
- Transformers 4.43.1
- Pytorch 2.2.2+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1 |