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mamung/
f7edcc63-fefc-4eae-b622-2e65f127d6b6

Name: f7edcc63-fefc-4eae-b622-2e65f127d6b6
Availability: InStock

generated_from_trainer

Maykeye/TinyLLama-v0

adapter

apache-2.0

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See axolotl config

axolotl version: 0.4.1

yaml

adapter: lora
base_model: Maykeye/TinyLLama-v0
bf16: true
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
  - 3f7f4544935ed721_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/3f7f4544935ed721_train_data.json
  type:
    field_input: choices
    field_instruction: question
    field_output: answer
    format: '{instruction} {input}'
    no_input_format: '{instruction}'
    system_format: '{system}'
    system_prompt: ''
debug: null
deepspeed: null
early_stopping_patience: null
eval_max_new_tokens: 256
eval_table_size: null
evals_per_epoch: 4
flash_attention: false
fp16: null
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 32
gradient_checkpointing: true
group_by_length: false
hub_model_id: mamung/f7edcc63-fefc-4eae-b622-2e65f127d6b6
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: 3
lora_alpha: 64
lora_dropout: 0.05
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 32
lora_target_linear: true
lora_target_modules:
- q_proj
- k_proj
- v_proj
- o_proj
lr_scheduler: cosine
max_grad_norm: 1
max_steps: 100
micro_batch_size: 2
mlflow_experiment_name: /tmp/3f7f4544935ed721_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 3
optim_args:
  adam_beta1: 0.9
  adam_beta2: 0.95
  adam_epsilon: 1.0e-05
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: 4
sequence_len: 2048
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: eddysang
wandb_mode: online
wandb_name: e72b4b00-3aa8-4e69-b8ea-e98f6a2460bf
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: e72b4b00-3aa8-4e69-b8ea-e98f6a2460bf
warmup_steps: 20
weight_decay: 0.02
xformers_attention: false

f7edcc63-fefc-4eae-b622-2e65f127d6b6

This model is a fine-tuned version of Maykeye/TinyLLama-v0 on the None dataset. It achieves the following results on the evaluation set:

Loss: 7.9312

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: 32
total_train_batch_size: 64
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=adam_beta1=0.9,adam_beta2=0.95,adam_epsilon=1e-05
lr_scheduler_type: cosine
lr_scheduler_warmup_steps: 20
training_steps: 5

Training results

Training Loss	Epoch	Step	Validation Loss
No log	0.6275	1	7.9386
No log	1.5294	2	7.9391
12.4178	2.4314	3	7.9329
12.4178	3.3333	4	7.9338
12.4178	4.2353	5	7.9312

Framework versions

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