Breeze-7B-Cantonese-v0.1 / axolotl-config.yml
kennylam's picture
First commit for axolotl-config.yml
0e08b7b
base_model: MediaTek-Research/Breeze-7B-Base-v0_1
model_type: MistralForCausalLM
tokenizer_type: LlamaTokenizer
is_mistral_derived_model: true
load_in_8bit: false
load_in_4bit: true
strict: false
datasets:
- path: hon9kon9ize/yue-alpaca
type: alpaca
- path: indiejoseph/wikipedia-translate-zhhk-zhcn
type:
system_prompt: ""
field_instruction: zh
field_output: yue
format: |-
[INST]
翻譯下面中文至粵語廣東話(Cantonese)。
{instruction}
[/INST]
- path: indiejoseph/wikipedia-zh-yue-summaries
type:
system_prompt: ""
field_instruction: content
field_output: summary
format: |-
[INST]
用粵語廣東話(Cantonese)總結一吓。
{instruction}
[/INST]
- path: indiejoseph/wikipedia-zh-yue-summaries
type:
system_prompt: ""
field_instruction: content
field_output: title
format: |-
[INST]
粵語廣東話(Cantonese), 呢篇嘢主題係咩?
{instruction}
[/INST]
- path: indiejoseph/wikipedia-zh-yue-summaries
type:
system_prompt: ""
field_instruction: content
field_output: category
format: |-
[INST]
粵語廣東話(Cantonese), 呢篇嘢講緊咩? 係咩分類?
{instruction}
[/INST]
- path: indiejoseph/wikipedia-zh-yue-qa
type:
system_prompt: ""
field_instruction: question
field_system: title
field_output: answer
format: |-
[INST]
粵語廣東話(Cantonese), 以下係關於「{system}」嘅問題。
{instruction}
[/INST]
dataset_prepared_path: last_run_prepared
val_set_size: 0.05
output_dir: loras/Breeze-7B-Cantonese-v0.1
save_safetensors: true
#eval_sample_packing: False
## You can optionally freeze the entire model and unfreeze a subset of parameters
unfrozen_parameters:
# - lm_head.*
# - model.embed_tokens.*
# - model.layers.2[0-9]+.block_sparse_moe.gate.*
# - model.layers.2[0-9]+.block_sparse_moe.experts.*
# - model.layers.3[0-9]+.block_sparse_moe.gate.*
# - model.layers.3[0-9]+.block_sparse_moe.experts.*
model_config:
output_router_logits: true
adapter: qlora
lora_model_dir:
sequence_len: 4096
sample_packing: true
pad_to_sequence_len: true
lora_r: 32
lora_alpha: 16
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: 4
micro_batch_size: 2
num_epochs: 1
optimizer: adamw_bnb_8bit
lr_scheduler: cosine
learning_rate: 0.0002
train_on_inputs: false
group_by_length: false
bf16: true
fp16: false
tf32: false
gradient_checkpointing: true
early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true
loss_watchdog_threshold: 5.0
loss_watchdog_patience: 3
warmup_steps: 10
evals_per_epoch: 4
eval_table_size:
eval_table_max_new_tokens: 128
saves_per_epoch: 1
debug:
deepspeed:
weight_decay: 0.0
fsdp:
fsdp_config:
special_tokens: