See axolotl config
axolotl version: 0.4.1
adapter: lora
base_model: zake7749/gemma-2-2b-it-chinese-kyara-dpo
bf16: auto
chat_template: llama3
dataloader_num_workers: 12
dataset_prepared_path: null
datasets:
- data_files:
- 785ff67fe820a49a_train_data.json
ds_type: json
format: custom
path: /workspace/input_data/785ff67fe820a49a_train_data.json
type:
field_instruction: init_prompt
field_output: init_response
format: '{instruction}'
no_input_format: '{instruction}'
system_format: '{system}'
system_prompt: ''
debug: null
deepspeed: null
device_map: auto
do_eval: true
early_stopping_patience: 3
eval_batch_size: 8
eval_max_new_tokens: 128
eval_steps: 150
eval_table_size: null
evals_per_epoch: null
flash_attention: true
fp16: false
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 2
gradient_checkpointing: true
group_by_length: true
hub_model_id: cimol/f7f537b2-9316-4f38-a52b-cadb60abb76c
hub_repo: null
hub_strategy: end
hub_token: null
learning_rate: 3e-5
load_in_4bit: false
load_in_8bit: false
local_rank: null
logging_steps: 15
lora_alpha: 128
lora_dropout: 0.1
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 64
lora_target_linear: true
lr_scheduler: cosine
lr_scheduler_warmup_steps: 50
max_grad_norm: 1.0
max_memory:
0: 75GB
max_steps: 1650
micro_batch_size: 8
mlflow_experiment_name: /tmp/785ff67fe820a49a_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 15
optim_args:
adam_beta1: 0.9
adam_beta2: 0.999
adam_epsilon: 1e-8
optimizer: adamw_torch
output_dir: miner_id_24
pad_to_sequence_len: false
resume_from_checkpoint: null
s2_attention: null
sample_packing: false
save_steps: 150
saves_per_epoch: null
seed: 17333
sequence_len: 1024
strict: false
tf32: true
tokenizer_type: AutoTokenizer
total_train_batch_size: 16
train_batch_size: 8
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.05
wandb_entity: null
wandb_mode: online
wandb_name: 56600945-b760-44be-9fdc-7a38b0eec0cc
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: 56600945-b760-44be-9fdc-7a38b0eec0cc
warmup_steps: 50
weight_decay: 0.1
xformers_attention: null
f7f537b2-9316-4f38-a52b-cadb60abb76c
This model is a fine-tuned version of zake7749/gemma-2-2b-it-chinese-kyara-dpo on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3602
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-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 17333
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=adam_beta1=0.9,adam_beta2=0.999,adam_epsilon=1e-8
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 50
- training_steps: 1650
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 0.0004 | 1 | 1.8429 |
| 0.499 | 0.0570 | 150 | 0.5961 |
| 0.4005 | 0.1139 | 300 | 0.5473 |
| 0.3805 | 0.1709 | 450 | 0.4914 |
| 0.3526 | 0.2278 | 600 | 0.4572 |
| 0.3628 | 0.2848 | 750 | 0.4255 |
| 0.3156 | 0.3418 | 900 | 0.4032 |
| 0.2911 | 0.3987 | 1050 | 0.3818 |
| 0.2412 | 0.4557 | 1200 | 0.3700 |
| 0.2719 | 0.5126 | 1350 | 0.3641 |
| 0.2914 | 0.5696 | 1500 | 0.3605 |
| 0.2707 | 0.6265 | 1650 | 0.3602 |
Framework versions
- PEFT 0.13.2
- Transformers 4.46.0
- Pytorch 2.5.0+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1
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Model tree for cimol/f7f537b2-9316-4f38-a52b-cadb60abb76c
Base model
google/gemma-2-2b Finetuned
google/gemma-2-2b-it Finetuned
zake7749/gemma-2-2b-it-chinese-kyara-dpo