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b5ead002-ee5a-4fc0-b7ec-0694cb4c63da

PEFT
Safetensors
llama
axolotl
Generated from Trainer
custom_code
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metadata
library_name: peft
base_model: NousResearch/Yarn-Llama-2-7b-64k
tags:
  - axolotl
  - generated_from_trainer
model-index:
  - name: b5ead002-ee5a-4fc0-b7ec-0694cb4c63da
    results: []

Built with Axolotl

See axolotl config

axolotl version: 0.4.1

adapter: lora
base_model: NousResearch/Yarn-Llama-2-7b-64k
bf16: true
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
  - ad09d962f07b40da_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/ad09d962f07b40da_train_data.json
  type:
    field_instruction: prompt
    field_output: response
    format: '{instruction}'
    no_input_format: '{instruction}'
    system_format: '{system}'
    system_prompt: ''
debug: null
deepspeed: null
device_map: auto
early_stopping_patience: 1
eval_max_new_tokens: 128
eval_steps: 25
eval_table_size: null
evals_per_epoch: null
flash_attention: false
fp16: false
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 4
gradient_checkpointing: true
group_by_length: false
hub_model_id: nttx/b5ead002-ee5a-4fc0-b7ec-0694cb4c63da
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: 128
lora_dropout: 0.05
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 64
lora_target_linear: true
lr_scheduler: cosine
max_memory:
  0: 70GB
max_steps: 50
micro_batch_size: 8
mlflow_experiment_name: /tmp/ad09d962f07b40da_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
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: null
wandb_mode: online
wandb_name: b5ead002-ee5a-4fc0-b7ec-0694cb4c63da
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: b5ead002-ee5a-4fc0-b7ec-0694cb4c63da
warmup_steps: 20
weight_decay: 0.0
xformers_attention: null

b5ead002-ee5a-4fc0-b7ec-0694cb4c63da

This model is a fine-tuned version of NousResearch/Yarn-Llama-2-7b-64k on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 1.0841

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: 8
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 4
  • 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: 20
  • training_steps: 50

Training results

Training Loss Epoch Step Validation Loss
4.5813 0.0063 1 1.2194
3.8048 0.1562 25 1.0970
4.5387 0.3125 50 1.0841

Framework versions

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