---
library_name: peft
license: apache-2.0
base_model: Qwen/Qwen2-0.5B-Instruct
tags:
- axolotl
- generated_from_trainer
model-index:
- name: 8783abb4-4863-4d35-96d0-38591b2d8490
results: []
---
[
](https://github.com/axolotl-ai-cloud/axolotl)
See axolotl config
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:
- a23a73113e5bcd49_train_data.json
ds_type: json
format: custom
path: /workspace/input_data/a23a73113e5bcd49_train_data.json
type:
field_instruction: title
field_output: content
format: '{instruction}'
no_input_format: '{instruction}'
system_format: '{system}'
system_prompt: ''
debug: null
device_map:
? ''
: 0,1,2,3,4,5,6,7
early_stopping_patience: 2
eval_max_new_tokens: 128
eval_steps: 100
eval_table_size: null
flash_attention: true
gradient_accumulation_steps: 8
gradient_checkpointing: true
group_by_length: false
hub_model_id: Alphatao/8783abb4-4863-4d35-96d0-38591b2d8490
hub_repo: null
hub_strategy: null
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: 128
lora_dropout: 0.1
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 64
lora_target_linear: true
lora_target_modules:
- q_proj
- k_proj
- v_proj
- o_proj
lr_scheduler: cosine
max_grad_norm: 1.0
max_steps: 5376
micro_batch_size: 4
mlflow_experiment_name: /tmp/a23a73113e5bcd49_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: 0.04787437763309077
wandb_entity: null
wandb_mode: online
wandb_name: 032a2798-2e45-4672-ba51-e28a8f853060
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: 032a2798-2e45-4672-ba51-e28a8f853060
warmup_steps: 10
weight_decay: 0.0
xformers_attention: null
```
# 8783abb4-4863-4d35-96d0-38591b2d8490
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: 1.7221
## 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: 5376
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 2.7661 | 0.0003 | 1 | 2.7781 |
| 2.4133 | 0.0322 | 100 | 2.3111 |
| 2.3796 | 0.0644 | 200 | 2.2424 |
| 2.1234 | 0.0965 | 300 | 2.2007 |
| 2.2836 | 0.1287 | 400 | 2.1683 |
| 2.1882 | 0.1609 | 500 | 2.1389 |
| 2.1209 | 0.1931 | 600 | 2.1168 |
| 1.9807 | 0.2253 | 700 | 2.0961 |
| 2.0003 | 0.2574 | 800 | 2.0819 |
| 1.8976 | 0.2896 | 900 | 2.0609 |
| 2.2535 | 0.3218 | 1000 | 2.0465 |
| 2.0813 | 0.3540 | 1100 | 2.0284 |
| 2.0837 | 0.3862 | 1200 | 2.0134 |
| 1.8759 | 0.4183 | 1300 | 2.0016 |
| 2.0767 | 0.4505 | 1400 | 1.9873 |
| 2.0557 | 0.4827 | 1500 | 1.9745 |
| 1.708 | 0.5149 | 1600 | 1.9607 |
| 2.0113 | 0.5471 | 1700 | 1.9480 |
| 2.0235 | 0.5792 | 1800 | 1.9328 |
| 1.9351 | 0.6114 | 1900 | 1.9223 |
| 1.796 | 0.6436 | 2000 | 1.9164 |
| 1.8088 | 0.6758 | 2100 | 1.9011 |
| 1.6286 | 0.7080 | 2200 | 1.8900 |
| 1.9361 | 0.7401 | 2300 | 1.8786 |
| 1.636 | 0.7723 | 2400 | 1.8669 |
| 1.8454 | 0.8045 | 2500 | 1.8579 |
| 1.9547 | 0.8367 | 2600 | 1.8472 |
| 1.5638 | 0.8689 | 2700 | 1.8384 |
| 1.611 | 0.9010 | 2800 | 1.8275 |
| 1.7571 | 0.9332 | 2900 | 1.8143 |
| 1.9847 | 0.9654 | 3000 | 1.8063 |
| 1.9508 | 0.9976 | 3100 | 1.7982 |
| 1.3798 | 1.0298 | 3200 | 1.7971 |
| 1.5009 | 1.0619 | 3300 | 1.7864 |
| 1.5614 | 1.0941 | 3400 | 1.7795 |
| 1.7675 | 1.1263 | 3500 | 1.7721 |
| 1.2293 | 1.1585 | 3600 | 1.7665 |
| 1.7646 | 1.1907 | 3700 | 1.7610 |
| 1.4301 | 1.2228 | 3800 | 1.7582 |
| 1.2718 | 1.2550 | 3900 | 1.7507 |
| 1.6806 | 1.2872 | 4000 | 1.7457 |
| 1.5779 | 1.3194 | 4100 | 1.7413 |
| 1.3326 | 1.3516 | 4200 | 1.7374 |
| 1.6239 | 1.3837 | 4300 | 1.7350 |
| 1.713 | 1.4159 | 4400 | 1.7322 |
| 1.5364 | 1.4481 | 4500 | 1.7300 |
| 1.2966 | 1.4803 | 4600 | 1.7277 |
| 1.5881 | 1.5125 | 4700 | 1.7258 |
| 1.2867 | 1.5447 | 4800 | 1.7244 |
| 1.6141 | 1.5768 | 4900 | 1.7233 |
| 1.6782 | 1.6090 | 5000 | 1.7233 |
| 1.7381 | 1.6412 | 5100 | 1.7224 |
| 1.6309 | 1.6734 | 5200 | 1.7222 |
| 1.6214 | 1.7056 | 5300 | 1.7221 |
### Framework versions
- PEFT 0.13.2
- Transformers 4.46.0
- Pytorch 2.5.0+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1