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Einstein-v4-phi2

Text Generation
Transformers
Safetensors
English
phi
axolotl
Generated from Trainer
phi2
einstein
instruct
finetune
chatml
gpt4
synthetic data
science
physics
chemistry
biology
math
conversational
custom_code
Eval Results
text-generation-inference
Inference Endpoints
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Einstein-v4-phi2 / README.md
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metadata
license: mit
base_model: microsoft/phi-2
tags:
  - axolotl
  - generated_from_trainer
model-index:
  - name: Einstein-v4-phi2
    results: []

Built with Axolotl

See axolotl config

axolotl version: 0.4.0

base_model: microsoft/phi-2
model_type: AutoModelForCausalLM
tokenizer_type: AutoTokenizer

load_in_8bit: false
load_in_4bit: false
strict: false

chat_template: chatml
datasets:
  - path: data/merged_all.json
    ds_type: json
    type: alpaca
    conversation: chatml

  - path: data/capybara_sharegpt.json
    ds_type: json
    type: sharegpt
    conversation: chatml

  - path: data/synthia-v1.3_sharegpt_12500.json
    ds_type: json
    type: sharegpt
    conversation: chatml  

  - path: data/cot_alpaca_gpt4_extracted_openhermes_2.5_sharegpt.json
    ds_type: json
    type: sharegpt
    conversation: chatml

  - path: data/slimorca_dedup_filtered_95k_sharegpt.json
    ds_type: json
    type: sharegpt
    conversation: chatml  

  - path: data/airoboros_3.2_without_contextual_slimorca_orca_sharegpt.json
    ds_type: json
    type: sharegpt
    conversation: chatml  

dataset_prepared_path: last_run_prepared
val_set_size: 0.005
output_dir: ./Einstein-v4-phi2-model

sequence_len: 2048
sample_packing: true
pad_to_sequence_len: true
eval_sample_packing: false

wandb_project: Einstein
wandb_entity:
wandb_watch:
wandb_name:
wandb_log_model:
hub_model_id: Weyaxi/Einstein-v4-phi2

save_safetensors: true

gradient_accumulation_steps: 4
micro_batch_size: 3
num_epochs: 2
optimizer: adamw_torch # adamw_bnb_8bit
lr_scheduler: cosine
learning_rate: 0.000005

train_on_inputs: false
group_by_length: false
bf16: true
fp16: false
tf32: false

gradient_checkpointing: true
early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true

warmup_steps: 10
evals_per_epoch: 2 # changed
eval_table_size:
eval_table_max_new_tokens: 128
saves_per_epoch: 4
debug:

deepspeed: zero3_bf16.json
weight_decay: 0.0
fsdp:
fsdp_config:
special_tokens:
  eos_token: "<|im_end|>"
  pad_token: "<|endoftext|>"
tokens:
  - "<|im_start|>"

Einstein-v4-phi2

This model is a fine-tuned version of microsoft/phi-2 on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.7362

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: 5e-06
  • train_batch_size: 3
  • eval_batch_size: 3
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 9
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 108
  • total_eval_batch_size: 27
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_steps: 10
  • num_epochs: 2

Training results

Training Loss Epoch Step Validation Loss
1.1232 0.0 1 1.0997
0.7597 0.5 545 0.7720
0.7232 1.0 1090 0.7451
0.7806 1.48 1635 0.7362

Framework versions

  • Transformers 4.38.2
  • Pytorch 2.1.2+cu118
  • Datasets 2.18.0
  • Tokenizers 0.15.0