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dimasik87/
22b05afc-5100-4d8e-849b-39843d793e1c

Name: 22b05afc-5100-4d8e-849b-39843d793e1c
Availability: InStock

generated_from_trainer

huggyllama/llama-7b

adapter

other

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See axolotl config

axolotl version: 0.4.1

yaml

adapter: lora
base_model: huggyllama/llama-7b
bf16: auto
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
  - e159c7177b77ec6f_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/e159c7177b77ec6f_train_data.json
  type:
    field_input: data
    field_instruction: criteria
    field_output: metadata
    format: '{instruction} {input}'
    no_input_format: '{instruction}'
    system_format: '{system}'
    system_prompt: ''
debug: null
deepspeed: null
early_stopping_patience: null
eval_max_new_tokens: 128
eval_table_size: null
evals_per_epoch: 4
flash_attention: true
fp16: true
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 4
gradient_checkpointing: true
group_by_length: false
hub_model_id: dimasik87/22b05afc-5100-4d8e-849b-39843d793e1c
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: 0.1
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: 25
micro_batch_size: 1
mlflow_experiment_name: /tmp/e159c7177b77ec6f_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
saves_per_epoch: 3
sequence_len: 2028
special_tokens:
  pad_token: </s>
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: 22b05afc-5100-4d8e-849b-39843d793e1c
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: 22b05afc-5100-4d8e-849b-39843d793e1c
warmup_steps: 10
weight_decay: 0.0
xformers_attention: null

22b05afc-5100-4d8e-849b-39843d793e1c

This model is a fine-tuned version of huggyllama/llama-7b on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.4823

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: 1
eval_batch_size: 1
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 4
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: 25

Training results

Training Loss	Epoch	Step	Validation Loss
1.0813	0.0001	1	1.2754
1.3021	0.0003	3	1.2664
0.9882	0.0006	6	1.1865
0.8609	0.0010	9	1.0022
0.6663	0.0013	12	0.7372
0.4392	0.0016	15	0.5888
0.4097	0.0019	18	0.5241
0.4966	0.0022	21	0.4919
0.7604	0.0026	24	0.4823

Framework versions

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