metadata
library_name: peft
license: apache-2.0
base_model: Qwen/Qwen2.5-14B-Instruct
tags:
- generated_from_trainer
model-index:
- name: outputs/lora-out
results: []
See axolotl config
axolotl version: 0.5.0
base_model: Qwen/Qwen2.5-14B-Instruct
trust_remote_code: true
load_in_8bit: false
load_in_4bit: false
strict: false
datasets:
- path: main_dataset_v1.json
type: alpaca
special_tokens:
bos_token:
eos_token: "<|im_end|>"
pad_token: "<|endoftext|>"
dataset_prepared_path:
val_set_size: 0.05
output_dir: ./outputs/lora-out
sequence_len: 1024
sample_packing: false
pad_to_sequence_len: true
adapter: lora
lora_model_dir:
lora_r: 8
lora_alpha: 16
lora_dropout: 0.05
lora_target_linear: true
lora_fan_in_fan_out:
lora_target_modules:
- gate_proj
- down_proj
- up_proj
- q_proj
- v_proj
- k_proj
- o_proj
wandb_project: dywoo_axolotl
wandb_entity: dywoo
wandb_watch:
wandb_run_id:
wandb_log_model:
gradient_accumulation_steps: 2
micro_batch_size: 2
num_epochs: 3
optimizer: paged_adamw_32bit
lr_scheduler: cosine
learning_rate: 0.00005
train_on_inputs:
group_by_length: false
bf16: true
fp16: false
tf32: false
gradient_checkpointing: true
early_stopping_patience:
logging_steps: 100
xformers_attention:
flash_attention: true
warmup_ratio: 0.01
eval_steps: 100
save_steps: 100
save_total_limit: 2
eval_sample_packing:
debug:
deepspeed:
weight_decay: 0.01
fsdp:
fsdp_config:
outputs/lora-out
This model is a fine-tuned version of Qwen/Qwen2.5-14B-Instruct on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0749
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: 5e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Use OptimizerNames.PAGED_ADAMW 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: 16
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 0.0019 | 1 | 0.3101 |
| 0.1179 | 0.1869 | 100 | 0.0830 |
| 0.0312 | 0.3738 | 200 | 0.0780 |
| 0.0276 | 0.5607 | 300 | 0.0743 |
| 0.0256 | 0.7477 | 400 | 0.0692 |
| 0.0222 | 0.9346 | 500 | 0.0705 |
| 0.0199 | 1.1215 | 600 | 0.0686 |
| 0.0174 | 1.3084 | 700 | 0.0695 |
| 0.015 | 1.4953 | 800 | 0.0702 |
| 0.0158 | 1.6822 | 900 | 0.0721 |
| 0.0147 | 1.8692 | 1000 | 0.0706 |
| 0.0139 | 2.0561 | 1100 | 0.0701 |
| 0.0097 | 2.2430 | 1200 | 0.0739 |
| 0.0099 | 2.4299 | 1300 | 0.0745 |
| 0.0097 | 2.6168 | 1400 | 0.0745 |
| 0.0107 | 2.8037 | 1500 | 0.0746 |
| 0.0093 | 2.9907 | 1600 | 0.0749 |
Framework versions
- PEFT 0.13.2
- Transformers 4.46.1
- Pytorch 2.3.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.3