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nttx/
e53f9f24-1143-4a09-b0e5-d2c1f5bc4add

generated_from_trainer

microsoft/phi-1_5

adapter

mit

Views

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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:
  - 66c805b3b6855143_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/66c805b3b6855143_train_data.json
  type:
    field_instruction: sentence1
    field_output: sentence2
    format: '{instruction}'
    no_input_format: '{instruction}'
    system_format: '{system}'
    system_prompt: ''
debug: null
deepspeed: null
device_map: auto
do_eval: true
early_stopping_patience: null
eval_batch_size: 4
eval_max_new_tokens: 128
eval_steps: null
eval_table_size: null
evals_per_epoch: null
flash_attention: true
fp16: null
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 4
gradient_checkpointing: true
group_by_length: true
hub_model_id: nttx/e53f9f24-1143-4a09-b0e5-d2c1f5bc4add
hub_repo: null
hub_strategy: end
hub_token: null
learning_rate: 0.0001
load_in_4bit: false
load_in_8bit: false
local_rank: null
logging_steps: 1
lora_alpha: 16
lora_dropout: 0.05
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 8
lora_target_linear: true
lr_scheduler: cosine
max_grad_norm: 1.0
max_memory:
  0: 75GB
max_steps: 200
micro_batch_size: 4
mlflow_experiment_name: /tmp/66c805b3b6855143_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 1
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: null
saves_per_epoch: null
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: d6c901d2-694d-4463-b3d7-6d30464aa28c
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: d6c901d2-694d-4463-b3d7-6d30464aa28c
warmup_steps: 5
weight_decay: 0.0
xformers_attention: null

e53f9f24-1143-4a09-b0e5-d2c1f5bc4add

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: 2.2809

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: 4
total_train_batch_size: 16
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: 5
training_steps: 200

Training results

Training Loss	Epoch	Step	Validation Loss
3.0457	0.3996	200	2.2809

Framework versions

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