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tarabukinivan/
b43c484f-1f39-4923-b536-18db258e2d8a

Name: b43c484f-1f39-4923-b536-18db258e2d8a
Availability: InStock

generated_from_trainer

elyza/Llama-3-ELYZA-JP-8B

adapter

llama3

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See axolotl config

axolotl version: 0.4.1

yaml

adapter: lora
base_model: elyza/Llama-3-ELYZA-JP-8B
bf16: auto
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
  - 8e9f6754d0b5829e_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/8e9f6754d0b5829e_train_data.json
  type:
    field_instruction: question
    field_output: answer
    format: '{instruction}'
    no_input_format: '{instruction}'
    system_format: '{system}'
    system_prompt: ''
debug: null
deepspeed: null
device: cuda
early_stopping_patience: null
eval_max_new_tokens: 128
eval_table_size: null
evals_per_epoch: 4
flash_attention: false
fp16: null
fsdp: null
fsdp_config:
  max_steps: 50
  weight_decay: 0.01
gradient_accumulation_steps: 4
gradient_checkpointing: false
group_by_length: false
hub_model_id: tarabukinivan/b43c484f-1f39-4923-b536-18db258e2d8a
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: 1
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_memory:
  0: 70GiB
max_steps: 10
micro_batch_size: 2
mlflow_experiment_name: /tmp/8e9f6754d0b5829e_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 3
optimizer: adamw_torch
output_dir: miner_id_24
pad_to_sequence_len: true
resume_from_checkpoint: null
s2_attention: null
sample_packing: false
save_steps: 25
sequence_len: 2048
special_tokens:
  pad_token: <|eot_id|>
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: b43c484f-1f39-4923-b536-18db258e2d8a
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: b43c484f-1f39-4923-b536-18db258e2d8a
warmup_steps: 10
weight_decay: 0.0
xformers_attention: null

b43c484f-1f39-4923-b536-18db258e2d8a

This model is a fine-tuned version of elyza/Llama-3-ELYZA-JP-8B on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.8620

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: 2
eval_batch_size: 2
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 8
optimizer: Use OptimizerNames.ADAMW_TORCH 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: 10
training_steps: 10

Training results

Training Loss	Epoch	Step	Validation Loss
1.3184	0.0010	1	1.3775
1.2625	0.0020	2	1.3745
1.4153	0.0029	3	1.3624
1.1229	0.0039	4	1.3268
1.2239	0.0049	5	1.2546
1.1991	0.0059	6	1.1703
0.9483	0.0069	7	1.0860
1.1308	0.0078	8	0.9987
1.0389	0.0088	9	0.9156
0.911	0.0098	10	0.8620

Framework versions

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