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infogep/
0ba4b684-9427-4445-bf2f-22e59cf8b99c

Name: 0ba4b684-9427-4445-bf2f-22e59cf8b99c
Availability: InStock

generated_from_trainer

heegyu/WizardVicuna2-13b-hf

adapter

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See axolotl config

axolotl version: 0.4.1

yaml

adapter: lora
base_model: heegyu/WizardVicuna2-13b-hf
bf16: auto
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
  - bc2adfd83bdd8a6f_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/bc2adfd83bdd8a6f_train_data.json
  type:
    field_instruction: query
    field_output: answer
    format: '{instruction}'
    no_input_format: '{instruction}'
    system_format: '{system}'
    system_prompt: ''
debug: null
deepspeed: null
device: cuda
early_stopping_patience: 1
eval_max_new_tokens: 128
eval_steps: 5
eval_table_size: null
evals_per_epoch: null
flash_attention: false
fp16: null
gradient_accumulation_steps: 4
gradient_checkpointing: true
gradient_clipping: 1.0
group_by_length: true
hub_model_id: infogep/0ba4b684-9427-4445-bf2f-22e59cf8b99c
hub_repo: null
hub_strategy: end
hub_token: null
learning_rate: 5.0e-05
load_in_4bit: false
load_in_8bit: false
local_rank: null
logging_steps: 3
lora_alpha: 16
lora_dropout: 0.05
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 8
lora_target_linear: true
lr_scheduler: cosine
max_steps: 30
micro_batch_size: 4
mlflow_experiment_name: /tmp/bc2adfd83bdd8a6f_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: 10
sequence_len: 1024
special_tokens:
  pad_token: </s>
strict: false
tf32: false
tokenizer_type: AutoTokenizer
train_on_inputs: true
trust_remote_code: true
val_set_size: 0.05
wandb_entity: null
wandb_mode: online
wandb_name: 1441ccf3-d1bc-42a4-8d4c-4e82f05841ca
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: 1441ccf3-d1bc-42a4-8d4c-4e82f05841ca
warmup_steps: 5
weight_decay: 0.0
xformers_attention: true

0ba4b684-9427-4445-bf2f-22e59cf8b99c

This model is a fine-tuned version of heegyu/WizardVicuna2-13b-hf on the None dataset. It achieves the following results on the evaluation set:

Loss: 1.6709

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: 4
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 4
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: 5
training_steps: 30

Training results

Training Loss	Epoch	Step	Validation Loss
No log	0.0002	1	1.8308
1.8494	0.0009	5	1.8264
1.739	0.0017	10	1.7769
1.6226	0.0026	15	1.7212
1.6468	0.0035	20	1.6888
1.8097	0.0044	25	1.6739
1.6232	0.0052	30	1.6709

Framework versions

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