You can deploy this model and start earning money today!

diaenra/
e4f6dbc2-ccf6-4ba5-9d91-de2b94199c0a

Name: e4f6dbc2-ccf6-4ba5-9d91-de2b94199c0a
Availability: InStock

generated_from_trainer

unsloth/gemma-2-9b

adapter

gemma

Views

No views yet

See axolotl config

axolotl version: 0.4.1

yaml

adapter: lora
base_model: unsloth/gemma-2-9b
bf16: auto
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
  - 0bc008faaedb9f44_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/0bc008faaedb9f44_train_data.json
  type:
    field_instruction: prompt
    field_output: test
    format: '{instruction}'
    no_input_format: '{instruction}'
    system_format: '{system}'
    system_prompt: ''
debug: null
deepspeed: null
early_stopping_patience: null
eval_max_new_tokens: 128
eval_steps: null
eval_table_size: null
evals_per_epoch: null
flash_attention: false
fp16: false
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 8
gradient_checkpointing: true
group_by_length: true
hub_model_id: diaenra/e4f6dbc2-ccf6-4ba5-9d91-de2b94199c0a
hub_repo: null
hub_strategy: checkpoint
hub_token: null
learning_rate: 0.0001
load_in_4bit: false
load_in_8bit: false
local_rank: null
logging_steps: 1
lora_alpha: 16
lora_dropout: 0.05
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 32
lora_target_linear: true
lr_scheduler: cosine
max_memory:
  0: 70GB
micro_batch_size: 4
mlflow_experiment_name: /tmp/0bc008faaedb9f44_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 2
optimizer: adamw_torch
output_dir: miner_id_24
pad_to_sequence_len: true
resume_from_checkpoint: null
s2_attention: null
sample_packing: false
save_steps: null
saves_per_epoch: null
sequence_len: 1024
strict: false
tf32: false
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.05
wandb_entity: diaenra-tao-miner
wandb_mode: online
wandb_name: 95cf6143-faa6-44fa-aa31-bd6c247f6df9
wandb_project: tao
wandb_run: diaenra
wandb_runid: 95cf6143-faa6-44fa-aa31-bd6c247f6df9
warmup_steps: 10
weight_decay: 0.0
xformers_attention: true

e4f6dbc2-ccf6-4ba5-9d91-de2b94199c0a

This model is a fine-tuned version of unsloth/gemma-2-9b on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.0760

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: 0.0001
train_batch_size: 4
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 32
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: 2

Training results

Training Loss	Epoch	Step	Validation Loss
0.0325	0.9846	48	0.1195
0.0613	1.9692	96	0.0760

Framework versions

PEFT 0.13.2
Transformers 4.46.0
Pytorch 2.5.0+cu124
Datasets 3.0.1
Tokenizers 0.20.1