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Alphatao/
02ea771b-5343-42ba-b784-88992ede2593

Name: 02ea771b-5343-42ba-b784-88992ede2593
Availability: InStock

generated_from_trainer

microsoft/phi-1_5

adapter

mit

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See axolotl config

axolotl version: 0.4.1

yaml

adapter: lora
base_model: microsoft/phi-1_5
bf16: true
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
  - e694fc7049de4f71_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/e694fc7049de4f71_train_data.json
  type:
    field_input: category
    field_instruction: style
    field_output: text
    format: '{instruction} {input}'
    no_input_format: '{instruction}'
    system_format: '{system}'
    system_prompt: ''
debug: null
device_map:
  ? ''
  : 0,1,2,3,4,5,6,7
early_stopping_patience: 2
eval_max_new_tokens: 128
eval_steps: 100
eval_table_size: null
flash_attention: false
gradient_accumulation_steps: 8
gradient_checkpointing: true
group_by_length: false
hub_model_id: Alphatao/02ea771b-5343-42ba-b784-88992ede2593
hub_repo: null
hub_strategy: null
hub_token: null
learning_rate: 0.0002
load_best_model_at_end: true
load_in_4bit: false
load_in_8bit: false
local_rank: null
logging_steps: 1
lora_alpha: 128
lora_dropout: 0.1
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 64
lora_target_linear: true
lora_target_modules:
- q_proj
- k_proj
- v_proj
- o_proj
lr_scheduler: cosine
max_grad_norm: 1.0
max_steps: 460
micro_batch_size: 4
mlflow_experiment_name: /tmp/e694fc7049de4f71_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 10
optimizer: adamw_bnb_8bit
output_dir: miner_id_24
pad_to_sequence_len: true
resume_from_checkpoint: null
s2_attention: null
sample_packing: false
save_steps: 100
sequence_len: 1024
special_tokens:
  pad_token: <|endoftext|>
strict: false
tf32: true
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.05
wandb_entity: null
wandb_mode: online
wandb_name: 85a01bbf-268f-4c59-a7b4-4d21809f7540
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: 85a01bbf-268f-4c59-a7b4-4d21809f7540
warmup_steps: 10
weight_decay: 0.0
xformers_attention: null

02ea771b-5343-42ba-b784-88992ede2593

This model is a fine-tuned version of microsoft/phi-1_5 on the None dataset. It achieves the following results on the evaluation set:

Loss: 3.3040

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: 4
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 32
optimizer: Use OptimizerNames.ADAMW_BNB 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: 460

Training results

Training Loss	Epoch	Step	Validation Loss
3.8677	0.0015	1	4.0304
3.3558	0.1547	100	3.3968
3.1905	0.3095	200	3.3459
3.346	0.4642	300	3.3147
3.2425	0.6190	400	3.3040

Framework versions

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