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dimasik1987
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d4a65b44-74ae-4eed-bcb3-2f0310c22f54

PEFT
Safetensors
llama
axolotl
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metadata
library_name: peft
license: llama2
base_model: codellama/CodeLlama-7b-Instruct-hf
tags:
  - axolotl
  - generated_from_trainer
model-index:
  - name: d4a65b44-74ae-4eed-bcb3-2f0310c22f54
    results: []

Built with Axolotl

See axolotl config

axolotl version: 0.4.1

adapter: lora
base_model: codellama/CodeLlama-7b-Instruct-hf
bf16: auto
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
  - 337dbfc6dbb39788_train_data.json
  ds_type: json
  field: question
  path: /workspace/input_data/337dbfc6dbb39788_train_data.json
  type: completion
debug: null
deepspeed: null
device: cuda
early_stopping_patience: null
eval_max_new_tokens: 128
eval_table_size: null
evals_per_epoch: 5
flash_attention: false
fp16: null
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 6
gradient_checkpointing: true
group_by_length: false
hub_model_id: dimasik1987/d4a65b44-74ae-4eed-bcb3-2f0310c22f54
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: 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_memory:
  0: 70GiB
max_steps: 50
micro_batch_size: 4
mlflow_experiment_name: /tmp/337dbfc6dbb39788_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
save_strategy: steps
sequence_len: 4056
special_tokens:
  pad_token: </s>
strict: false
tf32: false
tokenizer_type: AutoTokenizer
torch_dtype: bfloat16
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.05
wandb_entity: null
wandb_mode: online
wandb_name: d4a65b44-74ae-4eed-bcb3-2f0310c22f54
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: d4a65b44-74ae-4eed-bcb3-2f0310c22f54
warmup_steps: 10
weight_decay: 0.01
xformers_attention: null

d4a65b44-74ae-4eed-bcb3-2f0310c22f54

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

  • Loss: nan

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: 6
  • total_train_batch_size: 24
  • 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: 50

Training results

Training Loss Epoch Step Validation Loss
0.0 0.0010 1 nan
0.0 0.0039 4 nan
0.0 0.0078 8 nan
0.0 0.0117 12 nan
0.0 0.0156 16 nan
0.0 0.0195 20 nan
0.0 0.0234 24 nan
0.0 0.0273 28 nan
0.0 0.0312 32 nan
0.0 0.0351 36 nan
0.0 0.0390 40 nan
0.0 0.0429 44 nan
0.0 0.0468 48 nan

Framework versions

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