s3nh/phi-1_5_dolly_instruction_polish-GGUF

Quantized GGUF model files for phi-1_5_dolly_instruction_polish from s3nh

Name	Quant method	Size
phi-1_5_dolly_instruction_polish.fp16.gguf	fp16	2.84 GB
phi-1_5_dolly_instruction_polish.q2_k.gguf	q2_k	612.98 MB
phi-1_5_dolly_instruction_polish.q3_k_m.gguf	q3_k_m	765.45 MB
phi-1_5_dolly_instruction_polish.q4_k_m.gguf	q4_k_m	918.31 MB
phi-1_5_dolly_instruction_polish.q5_k_m.gguf	q5_k_m	1.06 GB
phi-1_5_dolly_instruction_polish.q6_k.gguf	q6_k	1.17 GB
phi-1_5_dolly_instruction_polish.q8_0.gguf	q8_0	1.51 GB

Original Model Card:

microsoft/phi_1.5 finetuned on s3nh/dolly_instruction_polish.

Finetuned with QLora, provided version is adapter merged with base model. Load in 4 bit, sequence length set to 1024.

axolotl config

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

load_in_8bit: false
load_in_4bit: true
strict: false

datasets:
  - path: s3nh/alpaca-dolly-instruction-only-polish
    type: alpaca

dataset_prepared_path:
val_set_size: 0.05
output_dir: ./phi-2-sft-out

sequence_len: 1024
sample_packing: false  # not CURRENTLY compatible with LoRAs
pad_to_sequence_len:

adapter: qlora
lora_model_dir:
lora_r: 64
lora_alpha: 32
lora_dropout: 0.05
lora_target_linear: true
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: 0.000003

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

gradient_checkpointing:
early_stopping_patience:
resume_from_checkpoint: false
local_rank:
logging_steps: 100
xformers_attention:
flash_attention: true

warmup_steps: 10
evals_per_epoch: 4
saves_per_epoch:
save_strategy: steps
save_steps: 5000
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|>"