Built with Axolotl

See axolotl config

axolotl version: 0.5.2

base_model: google/gemma-2-2b-it
hub_model_id: kweinmeister/gemma-2-2b-it-dolly-15k

load_in_8bit: false
load_in_4bit: true
strict: false

datasets:
  - path: databricks/databricks-dolly-15k
    type:
      field_instruction: instruction       
      field_input: context
      field_output: response
val_set_size: 0.05

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

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

wandb_project: gemma-2-2b-it-dolly-15k
wandb_entity:
wandb_watch:
wandb_name:
wandb_log_model:

gradient_accumulation_steps: 4
micro_batch_size: 1
num_epochs: 1
optimizer: adamw_torch
lr_scheduler: cosine
learning_rate: 0.0002

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

gradient_checkpointing: true
gradient_checkpointing_kwargs:
  use_reentrant: true
early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: false

warmup_steps: 10
evals_per_epoch: 4
saves_per_epoch: 1
debug:
deepspeed: deepspeed_configs/zero1.json
weight_decay: 0.0
fsdp:
fsdp_config:
special_tokens:
output_dir: "/mnt/disks/gcs/axolotl/runs/google--gemma-2-2b-it-20250101-144050/out/"
dataset_prepared_path: "/mnt/disks/gcs/axolotl/last_run_prepared"

gemma-2-2b-it-dolly-15k

This model is a fine-tuned version of google/gemma-2-2b-it on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 1.7389

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: 0.0002
  • train_batch_size: 1
  • eval_batch_size: 1
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 2
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 8
  • total_eval_batch_size: 2
  • optimizer: Use OptimizerNames.ADAMW_TORCH 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: 10
  • num_epochs: 1

Training results

Training Loss Epoch Step Validation Loss
5.7033 0.0061 1 5.5100
1.8197 0.2492 41 1.8752
1.6386 0.4985 82 1.7666
1.7346 0.7477 123 1.7436
1.7742 0.9970 164 1.7389

Framework versions

  • PEFT 0.13.2
  • Transformers 4.46.3
  • Pytorch 2.4.1+cu124
  • Datasets 3.1.0
  • Tokenizers 0.20.3
Downloads last month
17
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Model tree for kweinmeister/gemma-2-2b-it-dolly-15k

Base model

google/gemma-2-2b
Adapter
(177)
this model

Dataset used to train kweinmeister/gemma-2-2b-it-dolly-15k