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metadata
license: other
library_name: peft
tags:
  - generated_from_trainer
base_model: microsoft/phi-2
model-index:
  - name: phi-2-sft-out
    results: []

Built with Axolotl

phi-2-sft-out

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: 1.2813

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: 3e-06
  • 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: 10
  • num_epochs: 4

Training results

Training Loss Epoch Step Validation Loss
No log 0.0 1 1.7973
1.9767 0.25 5290 1.4832
1.8474 0.5 10580 1.4356
1.8121 0.75 15870 1.4022
1.8333 1.0 21160 1.3678
1.6601 1.25 26450 1.3508
1.5452 1.5 31740 1.3357
1.7381 1.75 37030 1.3191
1.6256 2.0 42320 1.3090
1.5521 2.25 47610 1.2961
1.8318 2.5 52900 1.2910
1.6761 2.75 58190 1.2901
1.6312 3.0 63480 1.2879
1.7003 3.25 68770 1.2820
1.6915 3.5 74060 1.2814
1.5757 3.75 79350 1.2813

Framework versions

  • Transformers 4.37.0.dev0
  • Pytorch 2.1.2+cu121
  • Datasets 2.16.0
  • Tokenizers 0.15.0

Training procedure

The following bitsandbytes quantization config was used during training:

  • quant_method: bitsandbytes
  • load_in_8bit: False
  • load_in_4bit: True
  • llm_int8_threshold: 6.0
  • llm_int8_skip_modules: None
  • llm_int8_enable_fp32_cpu_offload: False
  • llm_int8_has_fp16_weight: False
  • bnb_4bit_quant_type: nf4
  • bnb_4bit_use_double_quant: True
  • bnb_4bit_compute_dtype: bfloat16

Framework versions

  • PEFT 0.6.0