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diaenra/
b40d6b63-b891-48a0-82c2-6be9b708c498

Name: b40d6b63-b891-48a0-82c2-6be9b708c498
Availability: InStock

generated_from_trainer

katuni4ka/tiny-random-olmo-hf

adapter

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See axolotl config

axolotl version: 0.4.1

yaml

adapter: lora
base_model: katuni4ka/tiny-random-olmo-hf
bf16: auto
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
  - 1fc5d11fd0e55e23_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/1fc5d11fd0e55e23_train_data.json
  type:
    field_instruction: question
    field_output: response_j
    format: '{instruction}'
    no_input_format: '{instruction}'
    system_format: '{system}'
    system_prompt: ''
debug: null
deepspeed: null
early_stopping_patience: null
eval_max_new_tokens: 128
eval_steps: null
eval_table_size: null
evals_per_epoch: null
flash_attention: false
fp16: false
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 8
gradient_checkpointing: true
group_by_length: true
hub_model_id: diaenra/b40d6b63-b891-48a0-82c2-6be9b708c498
hub_repo: null
hub_strategy: checkpoint
hub_token: null
learning_rate: 0.0001
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: 32
lora_target_linear: true
lr_scheduler: cosine
max_memory:
  0: 70GB
micro_batch_size: 4
mlflow_experiment_name: /tmp/1fc5d11fd0e55e23_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: null
saves_per_epoch: null
sequence_len: 1024
strict: false
tf32: false
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.05
wandb_entity: diaenra-tao-miner
wandb_mode: online
wandb_name: 057bdd6f-f294-4a2a-9d03-12aa6222bebc
wandb_project: tao
wandb_run: diaenra
wandb_runid: 057bdd6f-f294-4a2a-9d03-12aa6222bebc
warmup_steps: 10
weight_decay: 0.0
xformers_attention: true

b40d6b63-b891-48a0-82c2-6be9b708c498

This model is a fine-tuned version of katuni4ka/tiny-random-olmo-hf on the None dataset. It achieves the following results on the evaluation set:

Loss: 10.5516

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: 4
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 32
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
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss
10.6027	0.9995	1608	10.5989
10.946	1.9997	3217	10.5568
9.4656	2.9986	4824	10.5516

Framework versions

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