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tuantmdev/
6b7fe6f4-3754-4379-bd1c-7c8aba8e47d6

generated_from_trainer

furiosa-ai/mlperf-gpt-j-6b

adapter

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See axolotl config

axolotl version: 0.4.1

yaml

adapter: lora
auto_find_batch_size: true
base_model: furiosa-ai/mlperf-gpt-j-6b
bf16: auto
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
  - b051361718f88ddb_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/b051361718f88ddb_train_data.json
  type:
    field_input: input
    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/6b7fe6f4-3754-4379-bd1c-7c8aba8e47d6
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: 400
micro_batch_size: 2
mlflow_experiment_name: /tmp/b051361718f88ddb_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: 966d5a5a-e872-4bc8-805b-43448f9e513a
wandb_project: Gradients-On-Demand
wandb_run: unknown
wandb_runid: 966d5a5a-e872-4bc8-805b-43448f9e513a
warmup_steps: 80
weight_decay: 0.0
xformers_attention: null

6b7fe6f4-3754-4379-bd1c-7c8aba8e47d6

This model is a fine-tuned version of furiosa-ai/mlperf-gpt-j-6b on the None dataset. It achieves the following results on the evaluation set:

Loss: 2.6080

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: 400

Training results

Training Loss	Epoch	Step	Validation Loss
No log	0.0001	1	4.5146
31.3262	0.0041	50	3.1604
24.4991	0.0082	100	2.9031
22.8594	0.0122	150	2.8066
21.7582	0.0163	200	2.7363
21.0565	0.0204	250	2.6649
21.0619	0.0245	300	2.6379
21.2316	0.0286	350	2.6141
20.9823	0.0326	400	2.6080

Framework versions

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