---
library_name: peft
license: llama3
base_model: WhiteRabbitNeo/Llama-3-WhiteRabbitNeo-8B-v2.0
tags:
- axolotl
- generated_from_trainer
model-index:
- name: b455d6fa-e4d0-4393-8f20-5915566a1c9f
  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
auto_find_batch_size: true
base_model: WhiteRabbitNeo/Llama-3-WhiteRabbitNeo-8B-v2.0
bf16: auto
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
  - e969e2e6ce61fbd8_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/e969e2e6ce61fbd8_train_data.json
  type:
    field_input: tools
    field_instruction: query
    field_output: answers
    format: '{instruction} {input}'
    no_input_format: '{instruction}'
    system_format: '{system}'
    system_prompt: ''
debug: null
deepspeed: null
do_eval: true
early_stopping_patience: 3
eval_max_new_tokens: 128
eval_steps: 50
evals_per_epoch: null
flash_attention: true
fp16: false
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 2
gradient_checkpointing: false
group_by_length: true
hub_model_id: lesso08/b455d6fa-e4d0-4393-8f20-5915566a1c9f
hub_repo: null
hub_strategy: checkpoint
hub_token: null
learning_rate: 0.000208
load_in_4bit: false
load_in_8bit: false
local_rank: null
logging_steps: 10
lora_alpha: 32
lora_dropout: 0.05
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 16
lora_target_linear: true
lr_scheduler: cosine
max_grad_norm: 1.0
max_steps: 500
micro_batch_size: 4
mlflow_experiment_name: /tmp/e969e2e6ce61fbd8_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 1
optimizer: adamw_bnb_8bit
output_dir: miner_id_24
pad_to_sequence_len: true
resume_from_checkpoint: null
s2_attention: null
sample_packing: false
save_steps: 50
saves_per_epoch: null
seed: 80
sequence_len: 512
strict: false
tf32: true
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.05
wandb_entity: null
wandb_mode: online
wandb_name: ad5e4146-bc69-4afe-a538-64cbda1f880d
wandb_project: 08a
wandb_run: your_name
wandb_runid: ad5e4146-bc69-4afe-a538-64cbda1f880d
warmup_steps: 50
weight_decay: 0.0
xformers_attention: null

```

</details><br>

# b455d6fa-e4d0-4393-8f20-5915566a1c9f

This model is a fine-tuned version of [WhiteRabbitNeo/Llama-3-WhiteRabbitNeo-8B-v2.0](https://huggingface.co/WhiteRabbitNeo/Llama-3-WhiteRabbitNeo-8B-v2.0) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0530

## 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: 0.000208
- train_batch_size: 4
- eval_batch_size: 4
- seed: 80
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 50
- training_steps: 500

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| No log        | 0.0001 | 1    | 0.8562          |
| 0.022         | 0.0073 | 50   | 0.1241          |
| 0.0156        | 0.0146 | 100  | 0.0792          |
| 0.0203        | 0.0219 | 150  | 0.0729          |
| 0.0199        | 0.0292 | 200  | 0.0639          |
| 0.0192        | 0.0365 | 250  | 0.0568          |
| 0.0315        | 0.0438 | 300  | 0.0574          |
| 0.0174        | 0.0511 | 350  | 0.0596          |
| 0.0152        | 0.0584 | 400  | 0.0531          |
| 0.0261        | 0.0657 | 450  | 0.0522          |
| 0.0201        | 0.0730 | 500  | 0.0530          |


### Framework versions

- PEFT 0.13.2
- Transformers 4.46.0
- Pytorch 2.5.0+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1