---
license: other
library_name: peft
tags:
- generated_from_trainer
base_model: meta-llama/Meta-Llama-3-8B-Instruct
model-index:
- name: workspace/llama3-8b-pippa
  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/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
<details><summary>See axolotl config</summary>

axolotl version: `0.4.0`
```yaml

base_model: meta-llama/Meta-Llama-3-8B-Instruct
model_type: LlamaForCausalLM
tokenizer_type: AutoTokenizer

load_in_8bit: false
load_in_4bit: true
strict: false

datasets:
#  - path: taozi555/bagel
#    type: sharegpt
  - path: MinervaAI/Aesir-Preview
    type: sharegpt
  - path: KaraKaraWitch/PIPPA-ShareGPT-formatted
    type: sharegpt
chat_template: chatml

dataset_prepared_path: last_run_prepared
val_set_size: 0.001
output_dir: /workspace/llama3-8b-pippa
adapter: qlora
lora_model_dir:

sequence_len: 8192
sample_packing: true
pad_to_sequence_len: true

lora_r: 32
lora_alpha: 16
lora_dropout: 0.05
lora_target_modules:
lora_target_linear: true
lora_fan_in_fan_out:
lora_modules_to_save:
  - embed_tokens
  - lm_head

wandb_project: waifu
wandb_entity:
wandb_watch:
wandb_run_id:
wandb_log_model:

gradient_accumulation_steps: 4
micro_batch_size: 2
num_epochs: 4
adam_beta2: 0.95
adam_epsilon: 0.00001
max_grad_norm: 1.0
lr_scheduler: cosine
learning_rate: 0.0002
optimizer: paged_adamw_32bit

train_on_inputs: false
group_by_length: false
bf16: auto
fp16:
tf32: false
#bfloat16: true

gradient_checkpointing: true
early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true

warmup_steps: 10

eval_steps: 100
eval_table_size:
eval_table_max_new_tokens:
eval_sample_packing: false
saves_per_epoch: 
save_steps: 100
save_total_limit: 2
debug:
#deepspeed: /workspace/axolotl/deepspeed_configs/zero3_bf16_cpuoffload_all.json
weight_decay: 0.1
fsdp:
fsdp_config:
special_tokens:
  eos_token: "<|im_end|>"
  pad_token: "<|im_end|>"
tokens:
  - "<|im_start|>"

```

</details><br>

# workspace/llama3-8b-pippa

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: 1.5946

## 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=(0.9,0.95) and epsilon=1e-05
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 4.6425        | 0.0   | 1    | 4.4372          |
| 1.9054        | 0.21  | 100  | 1.6499          |
| 1.6536        | 0.41  | 200  | 1.6101          |
| 1.7332        | 0.62  | 300  | 1.5973          |
| 1.7975        | 0.82  | 400  | 1.6079          |
| 1.669         | 1.01  | 500  | 1.5992          |
| 1.5612        | 1.21  | 600  | 1.5926          |
| 1.6936        | 1.42  | 700  | 1.5868          |
| 1.6197        | 1.62  | 800  | 1.5707          |
| 1.6831        | 1.83  | 900  | 1.5690          |
| 1.4055        | 2.02  | 1000 | 1.5902          |
| 1.4736        | 2.22  | 1100 | 1.5987          |
| 1.4137        | 2.43  | 1200 | 1.5899          |
| 1.4527        | 2.63  | 1300 | 1.5854          |
| 1.507         | 2.84  | 1400 | 1.5814          |
| 1.4538        | 3.03  | 1500 | 1.5900          |
| 1.4501        | 3.24  | 1600 | 1.5938          |
| 1.3612        | 3.44  | 1700 | 1.5928          |
| 1.4801        | 3.65  | 1800 | 1.5922          |
| 1.3502        | 3.85  | 1900 | 1.5946          |


### Framework versions

- PEFT 0.10.0
- Transformers 4.40.0.dev0
- Pytorch 2.2.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0