Files
axolotl/examples/gemma2/reward-model.yaml
2024-10-13 15:11:13 -04:00

64 lines
1.1 KiB
YAML

base_model: google/gemma-2-2b
model_type: AutoModelForSequenceClassification
tokenizer_type: AutoTokenizer
load_in_8bit: false
load_in_4bit: false
strict: false
reward_model: true
chat_template: gemma
datasets:
- path: argilla/distilabel-intel-orca-dpo-pairs
type: bradley_terry.chat_template
val_set_size: 0.0
output_dir: ./outputs/out
remove_unused_columns: false
sequence_len: 2048
sample_packing: false
eval_sample_packing: false
pad_to_sequence_len: true
wandb_project:
wandb_entity:
wandb_watch:
wandb_name:
wandb_log_model:
gradient_accumulation_steps: 4
micro_batch_size: 2
num_epochs: 4
optimizer: adamw_bnb_8bit
lr_scheduler: cosine
learning_rate: 0.0002
train_on_inputs: false
group_by_length: false
bf16: true
fp16:
tf32: true
gradient_checkpointing: true
gradient_checkpointing_kwargs:
use_reentrant: false
early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true
warmup_ratio: 0.1
evals_per_epoch:
eval_table_size:
eval_max_new_tokens: 128
saves_per_epoch: 1
debug:
deepspeed:
weight_decay: 0.0
fsdp:
fsdp_config:
special_tokens: