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dimasik1987
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b0ac19e9-97b9-4fb4-aa79-8d09232f0582

PEFT
Safetensors
llama
axolotl
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b0ac19e9-97b9-4fb4-aa79-8d09232f0582 / README.md
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metadata
library_name: peft
base_model: MNC-Jihun/Mistral-7B-AO-u0.5-b2-ver0.4
tags:
  - axolotl
  - generated_from_trainer
model-index:
  - name: b0ac19e9-97b9-4fb4-aa79-8d09232f0582
    results: []

Built with Axolotl

See axolotl config

axolotl version: 0.4.1

adapter: lora
base_model: MNC-Jihun/Mistral-7B-AO-u0.5-b2-ver0.4
bf16: auto
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
  - bed1b0035ed3c630_train_data.json
  ds_type: json
  field: text
  path: /workspace/input_data/bed1b0035ed3c630_train_data.json
  type: completion
debug: null
deepspeed: null
early_stopping_patience: null
eval_max_new_tokens: 128
eval_table_size: null
flash_attention: false
fp16: true
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 8
gradient_checkpointing: true
group_by_length: false
hub_model_id: dimasik1987/b0ac19e9-97b9-4fb4-aa79-8d09232f0582
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: 32
lora_dropout: 0.1
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 16
lora_target_linear: true
lr_scheduler: cosine
max_memory:
  0: 74GiB
max_steps: 50
micro_batch_size: 2
mlflow_experiment_name: /tmp/bed1b0035ed3c630_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: 2048
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: b0ac19e9-97b9-4fb4-aa79-8d09232f0582
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: b0ac19e9-97b9-4fb4-aa79-8d09232f0582
warmup_ratio: 0.05
weight_decay: 0.01
xformers_attention: true

b0ac19e9-97b9-4fb4-aa79-8d09232f0582

This model is a fine-tuned version of MNC-Jihun/Mistral-7B-AO-u0.5-b2-ver0.4 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: 0.0002
  • train_batch_size: 2
  • eval_batch_size: 2
  • seed: 42
  • gradient_accumulation_steps: 8
  • total_train_batch_size: 16
  • 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: 2
  • training_steps: 50

Training results

Training Loss Epoch Step Validation Loss
0.0 0.9895 47 nan
0.0 1.0526 50 nan

Framework versions

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