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tuantmdev/
b019dbd1-c1df-4f82-b1c5-f37f3af8dedc

Name: b019dbd1-c1df-4f82-b1c5-f37f3af8dedc
Availability: InStock

generated_from_trainer

Qwen/Qwen2-7B-Instruct

adapter

apache-2.0

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See axolotl config

axolotl version: 0.4.1

yaml

adapter: lora
auto_find_batch_size: true
base_model: Qwen/Qwen2-7B-Instruct
bf16: auto
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
  - bd57acaff8182e57_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/bd57acaff8182e57_train_data.json
  type:
    field_input: testcase
    field_instruction: instruction
    field_output: output
    format: '{instruction} {input}'
    no_input_format: '{instruction}'
    system_format: '{system}'
    system_prompt: ''
debug: null
deepspeed: null
early_stopping_patience: 3
eval_max_new_tokens: 128
eval_steps: 50
eval_table_size: null
flash_attention: false
fp16: null
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 8
gradient_checkpointing: false
group_by_length: true
hub_model_id: tuantmdev/b019dbd1-c1df-4f82-b1c5-f37f3af8dedc
hub_repo: null
hub_strategy: checkpoint
hub_token: null
learning_rate: 1e-4
load_in_4bit: false
load_in_8bit: false
local_rank: null
logging_steps: 40
lora_alpha: 64
lora_dropout: 0.05
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 32
lora_target_linear: true
lr_scheduler: cosine
max_grad_norm: 1.0
max_steps: 200
micro_batch_size: 2
mlflow_experiment_name: /tmp/bd57acaff8182e57_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
save_strategy: steps
sequence_len: 512
strict: false
tf32: false
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.05
wandb_entity: null
wandb_mode: online
wandb_name: e572fc41-d502-496e-a750-44cde70ec9e4
wandb_project: Gradients-On-Demand
wandb_run: unknown
wandb_runid: e572fc41-d502-496e-a750-44cde70ec9e4
warmup_steps: 80
weight_decay: 0.0
xformers_attention: null

b019dbd1-c1df-4f82-b1c5-f37f3af8dedc

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

Loss: 0.1894

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: 0.0001
train_batch_size: 2
eval_batch_size: 2
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 16
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: 80
training_steps: 200

Training results

Training Loss	Epoch	Step	Validation Loss
No log	0.0001	1	0.6745
0.3072	0.0071	50	0.1995
0.2122	0.0143	100	0.1972
0.1918	0.0214	150	0.1909
0.1802	0.0285	200	0.1894

Framework versions

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