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Phasmid-2_v2

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metadata
license: mit
base_model: microsoft/phi-2
tags:
  - axolotl
  - generated_from_trainer
model-index:
  - name: Phasmid-2_v2
    results: []

Built with Axolotl

See axolotl config

axolotl version: 0.3.0

base_model: microsoft/phi-2
model_type: PhiForCausalLM
tokenizer_type: AutoTokenizer
is_llama_derived_model: false
trust_remote_code: true

load_in_8bit: false
load_in_4bit: false
strict: false

datasets:
  - path: SE6446/SE6446_phasmid_ds
    type: completion

hub_model_id: SE6446/Phasmid-2_v2
hub_strategy: every_save
use_auth_token: true
dataset_prepared_path: /phasmid-2-ds-path
val_set_size: 0.05
output_dir: ./phasmid-sft-out

sequence_len: 2048
sample_packing: true
pad_to_sequence_len:

adapter:
lora_model_dir:
lora_r:
lora_alpha:
lora_dropout:
lora_target_linear:
lora_fan_in_fan_out:

wandb_project: 
wandb_entity: 
wandb_watch:
wandb_name: 
wandb_log_model:

gradient_accumulation_steps: 1
micro_batch_size: 1
num_epochs: 4
optimizer: adamw_torch
adam_beta2: 0.95
adam_epsilon: 0.00001
max_grad_norm: 1.0
lr_scheduler: cosine
learning_rate: 0.0003

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

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

warmup_steps: 100
evals_per_epoch: 4
saves_per_epoch: 1
debug:
deepspeed:
weight_decay: 0.1
fsdp:
fsdp_config:
resize_token_embeddings_to_32x: true
special_tokens:
  bos_token: "<|endoftext|>"
  eos_token: "<|endoftext|>"
  unk_token: "<|endoftext|>"
  pad_token: "<|endoftext|>"

Phasmid-2_v2

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: 2.2924

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: 0.0003
  • train_batch_size: 1
  • eval_batch_size: 1
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-05
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_steps: 100
  • num_epochs: 4

Training results

Training Loss Epoch Step Validation Loss
2.3313 0.0 1 2.1374
2.5755 0.25 1319 2.5281
2.4864 0.5 2638 2.5314
2.0961 0.75 3957 2.4697
2.6547 1.0 5276 2.4213
2.1235 1.24 6595 2.3926
1.8875 1.49 7914 2.3233
0.9059 1.74 9233 2.2590
2.2046 1.99 10552 2.1985
1.1938 2.23 11871 2.2555
1.1425 2.48 13190 2.2393
0.6688 2.73 14509 2.2237
1.1111 2.98 15828 2.2126
0.651 3.21 17147 2.2859
0.8669 3.46 18466 2.2914
0.4149 3.71 19785 2.2924

Framework versions

  • Transformers 4.37.0.dev0
  • Pytorch 2.0.1+cu118
  • Datasets 2.16.1
  • Tokenizers 0.15.0