---
library_name: peft
license: apache-2.0
base_model: unsloth/Qwen2.5-1.5B-Instruct
tags:
- axolotl
- generated_from_trainer
model-index:
- name: 84afe1d4-4257-4eb1-972d-6df752fb4b25
  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: true
base_model: unsloth/Qwen2.5-1.5B-Instruct
bf16: auto
chat_template: llama3
dataset_prepared_path: null
dataset_processes: 6
datasets:
- data_files:
  - f498211ddfc39ad0_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/f498211ddfc39ad0_train_data.json
  type:
    field_instruction: text
    field_output: text_description
    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: 200
eval_table_size: null
evals_per_epoch: null
flash_attention: true
fp16: false
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 4
gradient_checkpointing: true
group_by_length: false
hub_model_id: error577/84afe1d4-4257-4eb1-972d-6df752fb4b25
hub_repo: null
hub_strategy: checkpoint
hub_token: null
learning_rate: 0.0002
load_in_4bit: true
load_in_8bit: false
local_rank: null
logging_steps: 1
lora_alpha: 64
lora_dropout: 0.1
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 32
lora_target_linear: true
lr_scheduler: cosine
max_grad_norm: 1.0
max_steps: null
micro_batch_size: 2
mlflow_experiment_name: /tmp/f498211ddfc39ad0_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: 200
sequence_len: 512
strict: false
tf32: false
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.005
wandb_entity: null
wandb_mode: online
wandb_name: c45098d1-819e-4d15-988b-1e7aa32b705d
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: c45098d1-819e-4d15-988b-1e7aa32b705d
warmup_steps: 30
weight_decay: 0.0
xformers_attention: null

```

</details><br>

# 84afe1d4-4257-4eb1-972d-6df752fb4b25

This model is a fine-tuned version of [unsloth/Qwen2.5-1.5B-Instruct](https://huggingface.co/unsloth/Qwen2.5-1.5B-Instruct) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5277

## 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: 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: 30
- num_epochs: 3

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 4.2872        | 0.0001 | 1    | 4.2889          |
| 0.8655        | 0.0105 | 200  | 0.6744          |
| 0.6984        | 0.0209 | 400  | 0.6216          |
| 0.6142        | 0.0314 | 600  | 0.6047          |
| 0.5007        | 0.0419 | 800  | 0.5945          |
| 0.7687        | 0.0523 | 1000 | 0.6034          |
| 0.7365        | 0.0628 | 1200 | 0.5816          |
| 0.6433        | 0.0732 | 1400 | 0.5778          |
| 0.7683        | 0.0837 | 1600 | 0.5629          |
| 0.5652        | 0.0942 | 1800 | 0.5651          |
| 0.643         | 0.1046 | 2000 | 0.5693          |
| 0.5288        | 0.1151 | 2200 | 0.5616          |
| 0.7206        | 0.1256 | 2400 | 0.5566          |
| 0.4707        | 0.1360 | 2600 | 0.5513          |
| 0.5978        | 0.1465 | 2800 | 0.5490          |
| 0.4808        | 0.1569 | 3000 | 0.5403          |
| 0.4192        | 0.1674 | 3200 | 0.5361          |
| 0.5707        | 0.1779 | 3400 | 0.5439          |
| 0.5219        | 0.1883 | 3600 | 0.5353          |
| 0.5931        | 0.1988 | 3800 | 0.5475          |
| 0.3744        | 0.2093 | 4000 | 0.5371          |
| 0.5987        | 0.2197 | 4200 | 0.5279          |
| 0.4643        | 0.2302 | 4400 | 0.5257          |
| 0.4355        | 0.2406 | 4600 | 0.5312          |
| 0.6844        | 0.2511 | 4800 | 0.5318          |
| 0.4962        | 0.2616 | 5000 | 0.5277          |


### Framework versions

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