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metadata
library_name: peft
license: apache-2.0
base_model: Qwen/Qwen2.5-0.5B
tags:
  - axolotl
  - generated_from_trainer
model-index:
  - name: a0e58d38-9c0c-4c70-a915-2a7d7f329b1d
    results: []

Built with Axolotl

See axolotl config

axolotl version: 0.4.1

adapter: lora
auto_find_batch_size: true
base_model: Qwen/Qwen2.5-0.5B
bf16: auto
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
  - a5b2f2f1fff7ad50_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/a5b2f2f1fff7ad50_train_data.json
  type:
    field_instruction: original_question
    field_output: response
    format: '{instruction}'
    no_input_format: '{instruction}'
    system_format: '{system}'
    system_prompt: ''
debug: null
deepspeed: null
do_eval: true
early_stopping_patience: 3
eval_max_new_tokens: 128
eval_steps: 50
evals_per_epoch: null
flash_attention: true
fp16: false
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 2
gradient_checkpointing: false
group_by_length: true
hub_model_id: lesso10/a0e58d38-9c0c-4c70-a915-2a7d7f329b1d
hub_repo: null
hub_strategy: checkpoint
hub_token: null
learning_rate: 0.00021
load_in_4bit: false
load_in_8bit: false
local_rank: null
logging_steps: 10
lora_alpha: 128
lora_dropout: 0.05
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 64
lora_target_linear: true
lr_scheduler: cosine
max_grad_norm: 1.0
max_steps: 500
micro_batch_size: 4
mlflow_experiment_name: /tmp/G.O.D/a5b2f2f1fff7ad50_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 1
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
saves_per_epoch: null
sequence_len: 512
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: 81effad2-52b8-4f10-b978-d03e0dc324cd
wandb_project: 10a
wandb_run: your_name
wandb_runid: 81effad2-52b8-4f10-b978-d03e0dc324cd
warmup_steps: 50
weight_decay: 0.0
xformers_attention: null

a0e58d38-9c0c-4c70-a915-2a7d7f329b1d

This model is a fine-tuned version of Qwen/Qwen2.5-0.5B on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2596

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: 0.00021
  • train_batch_size: 4
  • eval_batch_size: 4
  • seed: 42
  • gradient_accumulation_steps: 2
  • 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: 50
  • training_steps: 500

Training results

Training Loss Epoch Step Validation Loss
No log 0.0000 1 0.3769
0.2684 0.0011 50 0.3158
0.3281 0.0021 100 0.3241
0.3242 0.0032 150 0.3167
0.2813 0.0043 200 0.3057
0.2835 0.0053 250 0.2960
0.2907 0.0064 300 0.2850
0.2737 0.0075 350 0.2704
0.2648 0.0085 400 0.2633
0.2715 0.0096 450 0.2601
0.3065 0.0107 500 0.2596

Framework versions

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