---
library_name: peft
license: apache-2.0
base_model: Qwen/Qwen3-8B-Base
tags:
- axolotl
- generated_from_trainer
model-index:
- name: 03d10d3d-d0de-4e3a-a192-1749f29583a3
  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: `0.10.0.dev0`
```yaml
adapter: lora
base_model: Qwen/Qwen3-8B-Base
bf16: true
datasets:
- data_files:
  - 45c346a7c1e52747_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/
  type:
    field_input: None
    field_instruction: instruct
    field_output: output
    field_system: None
    format: None
    no_input_format: None
    system_format: '{system}'
    system_prompt: None
eval_max_new_tokens: 128
evals_per_epoch: 4
flash_attention: false
fp16: false
gradient_accumulation_steps: 1
gradient_checkpointing: true
group_by_length: true
hub_model_id: apriasmoro/03d10d3d-d0de-4e3a-a192-1749f29583a3
learning_rate: 0.0002
load_in_4bit: false
logging_steps: 10
lora_alpha: 16
lora_dropout: 0.05
lora_fan_in_fan_out: false
lora_r: 8
lora_target_linear: true
lr_scheduler: cosine
max_steps: 14
micro_batch_size: 16
mlflow_experiment_name: /tmp/45c346a7c1e52747_train_data.json
output_dir: llama3_lora_output
rl: null
sample_packing: true
save_steps: 6
sequence_len: 2048
tf32: true
tokenizer_type: AutoTokenizer
train_on_inputs: true
trl: null
trust_remote_code: true
wandb_name: c732d2b4-46df-4ed8-83ee-7525f648965f
wandb_project: Gradients-On-Demand
wandb_run: llama3_h200_run
wandb_runid: c732d2b4-46df-4ed8-83ee-7525f648965f
warmup_steps: 100
weight_decay: 0.01

```

</details><br>

# 03d10d3d-d0de-4e3a-a192-1749f29583a3

This model is a fine-tuned version of [Qwen/Qwen3-8B-Base](https://huggingface.co/Qwen/Qwen3-8B-Base) on an unknown 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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: 100
- training_steps: 14

### Training results



### Framework versions

- PEFT 0.15.2
- Transformers 4.51.3
- Pytorch 2.5.1+cu124
- Datasets 3.5.1
- Tokenizers 0.21.1