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vmpsergio/
93565a03-9e1e-47b6-a50c-5fdf42ca35ff

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: auto
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
  - 333d08eefc564d5d_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/333d08eefc564d5d_train_data.json
  type:
    field_input: author
    field_instruction: title
    field_output: text
    format: '{instruction} {input}'
    no_input_format: '{instruction}'
    system_format: '{system}'
    system_prompt: ''
debug: null
deepspeed: null
device: cuda
early_stopping_patience: 1
eval_max_new_tokens: 128
eval_steps: 5
eval_table_size: null
evals_per_epoch: null
flash_attention: false
fp16: null
gradient_accumulation_steps: 4
gradient_checkpointing: true
group_by_length: false
hub_model_id: vmpsergio/93565a03-9e1e-47b6-a50c-5fdf42ca35ff
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: 3
lora_alpha: 32
lora_dropout: 0.05
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 16
lora_target_linear: true
lr_scheduler: cosine
max_memory:
  0: 78GiB
max_steps: 30
micro_batch_size: 2
mlflow_experiment_name: /tmp/333d08eefc564d5d_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 1
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: 10
sequence_len: 1024
special_tokens:
  pad_token: <|endoftext|>
strict: false
tf32: false
tokenizer_type: AutoTokenizer
train_on_inputs: true
trust_remote_code: true
val_set_size: 0.05
wandb_entity: null
wandb_mode: online
wandb_name: 413464a1-3ade-4d49-8176-c483c02b0fa7
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: 413464a1-3ade-4d49-8176-c483c02b0fa7
warmup_steps: 10
weight_decay: 0.01
xformers_attention: true

93565a03-9e1e-47b6-a50c-5fdf42ca35ff

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: 3.5986

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: 4
total_train_batch_size: 8
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: 30

Training results

Training Loss	Epoch	Step	Validation Loss
No log	0.0017	1	3.8429
3.677	0.0085	5	3.8152
3.7163	0.0171	10	3.7216
3.6628	0.0256	15	3.6578
3.3834	0.0342	20	3.6187
3.556	0.0427	25	3.6024
3.5184	0.0513	30	3.5986

Framework versions

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