---
library_name: peft
license: other
base_model: Qwen/Qwen2.5-3B-Instruct
tags:
- axolotl
- generated_from_trainer
model-index:
- name: 5981d3ad-273d-4654-ac2a-1505f39265e5
  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/Qwen2.5-3B-Instruct
bf16: true
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
  - cdb41d125efc324c_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/cdb41d125efc324c_train_data.json
  type:
    field_input: text
    field_instruction: query
    field_output: title
    format: '{instruction} {input}'
    no_input_format: '{instruction}'
    system_format: '{system}'
    system_prompt: ''
debug: null
deepspeed: null
eval_max_new_tokens: 128
eval_table_size: null
evals_per_epoch: 4
flash_attention: false
fp16: false
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 8
gradient_checkpointing: true
group_by_length: true
hub_model_id: dsakerkwq/5981d3ad-273d-4654-ac2a-1505f39265e5
learning_rate: 0.0002
load_in_4bit: false
load_in_8bit: false
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_memory:
  0: 75GiB
max_steps: 30
micro_batch_size: 2
mlflow_experiment_name: /tmp/cdb41d125efc324c_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 3
optimizer: adamw_torch
output_dir: miner_id_24
pad_to_sequence_len: true
s2_attention: false
sample_packing: false
saves_per_epoch: 4
sequence_len: 2048
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: 5981d3ad-273d-4654-ac2a-1505f39265e5
wandb_project: Gradients-On-Demand
wandb_runid: 5981d3ad-273d-4654-ac2a-1505f39265e5
warmup_steps: 100
weight_decay: 0.01
xformers_attention: false

```

</details><br>

# 5981d3ad-273d-4654-ac2a-1505f39265e5

This model is a fine-tuned version of [Qwen/Qwen2.5-3B-Instruct](https://huggingface.co/Qwen/Qwen2.5-3B-Instruct) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.8001

## 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: 8
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH 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: 30

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 2.4752        | 0.0000 | 1    | 3.6806          |
| 2.5345        | 0.0001 | 3    | 3.6822          |
| 2.5842        | 0.0002 | 6    | 3.6796          |
| 2.3758        | 0.0003 | 9    | 3.6679          |
| 3.1233        | 0.0004 | 12   | 3.6322          |
| 3.0729        | 0.0005 | 15   | 3.5695          |
| 3.3151        | 0.0006 | 18   | 3.4620          |
| 2.8179        | 0.0007 | 21   | 3.2984          |
| 2.7142        | 0.0008 | 24   | 3.1075          |
| 2.7692        | 0.0009 | 27   | 2.9502          |
| 2.3591        | 0.0011 | 30   | 2.8001          |


### Framework versions

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