---
library_name: peft
license: apache-2.0
base_model: Qwen/Qwen2-0.5B-Instruct
tags:
- axolotl
- generated_from_trainer
model-index:
- name: c31a0826-774c-48af-86bb-629bd7ef2583
  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: Qwen/Qwen2-0.5B-Instruct
bf16: true
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
  - c64ff0d01392d1e4_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/c64ff0d01392d1e4_train_data.json
  type:
    field_instruction: prompt_type
    field_output: prompt_text
    format: '{instruction}'
    no_input_format: '{instruction}'
    system_format: '{system}'
    system_prompt: ''
debug: null
deepspeed: null
early_stopping_patience: 2
eval_max_new_tokens: 128
eval_steps: 100
eval_table_size: null
flash_attention: true
fp16: null
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 8
gradient_checkpointing: true
group_by_length: false
hub_model_id: Alphatao/c31a0826-774c-48af-86bb-629bd7ef2583
hub_repo: null
hub_strategy: checkpoint
hub_token: null
learning_rate: 0.0002
load_best_model_at_end: true
load_in_4bit: false
load_in_8bit: false
local_rank: null
logging_steps: 1
lora_alpha: 32
lora_dropout: 0.05
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 16
lora_target_linear: true
lora_target_modules:
- q_proj
- k_proj
- v_proj
lr_scheduler: cosine
max_grad_norm: 1.0
max_steps: 8832
micro_batch_size: 4
mlflow_experiment_name: /tmp/c64ff0d01392d1e4_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 2
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: 100
sequence_len: 1024
strict: false
tf32: true
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.04
wandb_entity: null
wandb_mode: online
wandb_name: fb46a0d2-7710-4f02-ba9b-a717c0c8c0cd
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: fb46a0d2-7710-4f02-ba9b-a717c0c8c0cd
warmup_steps: 10
weight_decay: 0.0
xformers_attention: null

```

</details><br>

# c31a0826-774c-48af-86bb-629bd7ef2583

This model is a fine-tuned version of [Qwen/Qwen2-0.5B-Instruct](https://huggingface.co/Qwen/Qwen2-0.5B-Instruct) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8095

## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- 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: 10
- training_steps: 3084

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 5.3671        | 0.0006 | 1    | 5.3415          |
| 3.1325        | 0.0649 | 100  | 3.3948          |
| 3.3967        | 0.1297 | 200  | 3.2506          |
| 2.9834        | 0.1946 | 300  | 3.1461          |
| 2.6376        | 0.2594 | 400  | 3.0808          |
| 3.4206        | 0.3243 | 500  | 2.9966          |
| 3.0461        | 0.3892 | 600  | 2.9330          |
| 2.2323        | 0.4540 | 700  | 2.8605          |
| 2.7525        | 0.5189 | 800  | 2.7908          |
| 2.8358        | 0.5838 | 900  | 2.7131          |
| 2.8312        | 0.6486 | 1000 | 2.6433          |
| 2.4678        | 0.7135 | 1100 | 2.5774          |
| 2.5489        | 0.7783 | 1200 | 2.5080          |
| 2.3458        | 0.8432 | 1300 | 2.4473          |
| 2.3761        | 0.9081 | 1400 | 2.3796          |
| 2.0236        | 0.9729 | 1500 | 2.3125          |
| 1.9383        | 1.0378 | 1600 | 2.2606          |
| 1.8816        | 1.1026 | 1700 | 2.1880          |
| 1.8313        | 1.1675 | 1800 | 2.1419          |
| 1.9847        | 1.2324 | 1900 | 2.0941          |
| 1.8436        | 1.2972 | 2000 | 2.0431          |
| 1.6931        | 1.3621 | 2100 | 2.0023          |
| 1.593         | 1.4269 | 2200 | 1.9543          |
| 1.8932        | 1.4918 | 2300 | 1.9170          |
| 2.0395        | 1.5567 | 2400 | 1.8831          |
| 1.7951        | 1.6215 | 2500 | 1.8598          |
| 1.5655        | 1.6864 | 2600 | 1.8419          |
| 1.2855        | 1.7513 | 2700 | 1.8256          |
| 1.4709        | 1.8161 | 2800 | 1.8161          |
| 1.7402        | 1.8810 | 2900 | 1.8116          |
| 1.7177        | 1.9458 | 3000 | 1.8095          |


### Framework versions

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