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Kromtao/
4f721fe7-b774-4f8f-a72c-090ac16182f2

Name: 4f721fe7-b774-4f8f-a72c-090ac16182f2
Availability: InStock

generated_from_trainer

Qwen/Qwen2.5-7B-Instruct

adapter

apache-2.0

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See axolotl config

axolotl version: 0.4.1

yaml

adapter: lora
base_model: Qwen/Qwen2.5-7B-Instruct
bf16: auto
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
  - 0286bf1fb786e50e_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/0286bf1fb786e50e_train_data.json
  type:
    field_instruction: instruct
    field_output: output
    format: '{instruction}'
    no_input_format: '{instruction}'
    system_format: '{system}'
    system_prompt: ''
debug: null
deepspeed: null
do_eval: true
early_stopping_patience: 3
eval_batch_size: 8
eval_max_new_tokens: 128
eval_steps: 300
evals_per_epoch: null
flash_attention: true
fp16: false
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 4
gradient_checkpointing: true
group_by_length: true
hub_model_id: Kromtao/4f721fe7-b774-4f8f-a72c-090ac16182f2
hub_repo: null
hub_strategy: checkpoint
hub_token: null
learning_rate: 0.0002
load_in_4bit: false
load_in_8bit: false
local_rank: null
logging_steps: 50
lora_alpha: 16
lora_dropout: 0.1
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 8
lora_target_linear: true
lr_scheduler: cosine
max_grad_norm: 1.0
max_steps: 900
micro_batch_size: 8
mlflow_experiment_name: /tmp/0286bf1fb786e50e_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 10
optimizer: adamw_torch_fused
output_dir: miner_id_24
pad_to_sequence_len: true
resume_from_checkpoint: null
s2_attention: null
sample_packing: false
save_steps: 300
saves_per_epoch: null
seed: 9101
sequence_len: 1024
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: ee8326f0-cf7d-4132-b79f-a64b0ac1b6e6
wandb_project: kr01
wandb_run: your_name
wandb_runid: ee8326f0-cf7d-4132-b79f-a64b0ac1b6e6
warmup_steps: 50
weight_decay: 0.1
xformers_attention: null

4f721fe7-b774-4f8f-a72c-090ac16182f2

This model is a fine-tuned version of Qwen/Qwen2.5-7B-Instruct on the None dataset. It achieves the following results on the evaluation set:

Loss: 1.0624

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: 8
eval_batch_size: 8
seed: 9101
gradient_accumulation_steps: 4
total_train_batch_size: 32
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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: 900

Training results

Training Loss	Epoch	Step	Validation Loss
No log	0.0004	1	2.6703
1.3561	0.1330	300	1.2345
1.1358	0.2660	600	1.0922
1.0593	0.3990	900	1.0624

Framework versions

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