---
library_name: peft
license: other
base_model: unsloth/Qwen2.5-3B-Instruct
tags:
- axolotl
- generated_from_trainer
model-index:
- name: 0642c68c-f36b-4f0e-bcb2-4ece686f1819
  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: qlora
auto_resume_from_checkpoints: false
base_model: unsloth/Qwen2.5-3B-Instruct
bf16: auto
chat_template: llama3
dataloader_num_workers: 12
dataset_prepared_path: null
datasets:
- data_files:
  - f9174ef8c17657b3_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/f9174ef8c17657b3_train_data.json
  type:
    field_instruction: problem
    field_output: solution
    format: '{instruction}'
    no_input_format: '{instruction}'
    system_format: '{system}'
    system_prompt: ''
debug: null
deepspeed: null
early_stopping_patience: 3
eval_max_new_tokens: 128
eval_steps: 50
eval_table_size: null
evals_per_epoch: null
flash_attention: true
fp16: null
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 16
gradient_checkpointing: true
group_by_length: true
hub_model_id: error577/0642c68c-f36b-4f0e-bcb2-4ece686f1819
hub_repo: null
hub_strategy: checkpoint
hub_token: null
learning_rate: 0.0003
load_in_4bit: true
load_in_8bit: false
local_rank: null
logging_steps: 1
lora_alpha: 16
lora_dropout: 0.3
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 8
lora_target_linear: true
lr_scheduler: cosine
max_grad_norm: 1.0
max_steps: null
micro_batch_size: 1
mlflow_experiment_name: /tmp/f9174ef8c17657b3_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 3
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
sequence_len: 512
strict: false
tf32: false
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.2
wandb_entity: null
wandb_mode: online
wandb_name: 27a11b9e-1b27-41d2-8b20-883cfcd3a2ce
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: 27a11b9e-1b27-41d2-8b20-883cfcd3a2ce
warmup_steps: 10
weight_decay: 0.01
xformers_attention: null

```

</details><br>

# 0642c68c-f36b-4f0e-bcb2-4ece686f1819

This model is a fine-tuned version of [unsloth/Qwen2.5-3B-Instruct](https://huggingface.co/unsloth/Qwen2.5-3B-Instruct) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6036

## 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: 0.0003
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 16
- 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
- num_epochs: 3

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.7495        | 0.0073 | 1    | 1.1676          |
| 0.5302        | 0.3663 | 50   | 0.6131          |
| 0.4153        | 0.7326 | 100  | 0.5930          |
| 0.6004        | 1.0989 | 150  | 0.5869          |
| 0.4271        | 1.4652 | 200  | 0.5827          |
| 0.4949        | 1.8315 | 250  | 0.5702          |
| 0.3123        | 2.1978 | 300  | 0.6170          |
| 0.5157        | 2.5641 | 350  | 0.6207          |
| 0.276         | 2.9304 | 400  | 0.6036          |


### Framework versions

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