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tuantmdev/
2a480960-5eb8-4da2-a718-9f1c92de74f4

Name: 2a480960-5eb8-4da2-a718-9f1c92de74f4
Availability: InStock

generated_from_trainer

TitanML/tiny-mixtral

adapter

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See axolotl config

axolotl version: 0.4.1

yaml

adapter: lora
auto_find_batch_size: true
base_model: TitanML/tiny-mixtral
bf16: auto
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
  - b0eb1467538f454b_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/b0eb1467538f454b_train_data.json
  type:
    field_input: QuestionText
    field_instruction: context
    field_output: question
    format: '{instruction} {input}'
    no_input_format: '{instruction}'
    system_format: '{system}'
    system_prompt: ''
debug: null
deepspeed: null
early_stopping_patience: 3
eval_max_new_tokens: 128
eval_steps: 50
eval_table_size: null
flash_attention: false
fp16: null
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 8
gradient_checkpointing: false
group_by_length: true
hub_model_id: tuantmdev/2a480960-5eb8-4da2-a718-9f1c92de74f4
hub_repo: null
hub_strategy: checkpoint
hub_token: null
learning_rate: 1e-4
load_in_4bit: false
load_in_8bit: false
local_rank: null
logging_steps: 40
lora_alpha: 64
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_grad_norm: 1.0
max_steps: 400
micro_batch_size: 2
mlflow_experiment_name: /tmp/b0eb1467538f454b_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 1
optimizer: adamw_bnb_8bit
output_dir: miner_id_24
pad_to_sequence_len: true
resume_from_checkpoint: null
s2_attention: null
sample_packing: false
save_steps: 50
save_strategy: steps
sequence_len: 512
special_tokens:
  pad_token: </s>
strict: false
tf32: false
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.05
wandb_entity: null
wandb_mode: online
wandb_name: 4b3c7b79-71f5-456e-ad87-f6e3f78d1a76
wandb_project: Gradients-On-Demand
wandb_run: unknown
wandb_runid: 4b3c7b79-71f5-456e-ad87-f6e3f78d1a76
warmup_steps: 80
weight_decay: 0.0
xformers_attention: null

2a480960-5eb8-4da2-a718-9f1c92de74f4

This model is a fine-tuned version of TitanML/tiny-mixtral on the None dataset. It achieves the following results on the evaluation set:

Loss: nan

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: 2
eval_batch_size: 2
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 16
optimizer: Use OptimizerNames.ADAMW_BNB 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: 80
training_steps: 400

Training results

Training Loss	Epoch	Step	Validation Loss
No log	0.0005	1	nan
0.0	0.0271	50	nan
0.0	0.0542	100	nan
0.0	0.0813	150	nan
0.0	0.1084	200	nan

Framework versions

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