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dzanbek/
bde6dd29-3283-4003-9e15-540c2b89c415

Name: bde6dd29-3283-4003-9e15-540c2b89c415
Availability: InStock

generated_from_trainer

HuggingFaceM4/tiny-random-LlamaForCausalLM

adapter

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See axolotl config

axolotl version: 0.4.1

yaml

adapter: lora
base_model: HuggingFaceM4/tiny-random-LlamaForCausalLM
bf16: auto
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
  - 01763be6c1e518c5_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/01763be6c1e518c5_train_data.json
  type:
    field_input: ctx
    field_instruction: activity_label
    field_output: label
    format: '{instruction} {input}'
    no_input_format: '{instruction}'
    system_format: '{system}'
    system_prompt: ''
debug: null
deepspeed: null
early_stopping_patience: null
eval_max_new_tokens: 128
eval_table_size: null
evals_per_epoch: 4
flash_attention: false
fp16: null
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 4
gradient_checkpointing: false
group_by_length: false
hub_model_id: dzanbek/bde6dd29-3283-4003-9e15-540c2b89c415
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: 32
lora_dropout: 0.05
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 16
lora_target_linear: true
lr_scheduler: cosine
max_steps: 20
micro_batch_size: 2
mlflow_experiment_name: /tmp/01763be6c1e518c5_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 3
optimizer: adamw_bnb_8bit
output_dir: miner_id_24
pad_to_sequence_len: true
resume_from_checkpoint: null
s2_attention: null
sample_packing: false
saves_per_epoch: 4
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: null
wandb_mode: online
wandb_name: bde6dd29-3283-4003-9e15-540c2b89c415
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: bde6dd29-3283-4003-9e15-540c2b89c415
warmup_steps: 10
weight_decay: 0.01
xformers_attention: true

bde6dd29-3283-4003-9e15-540c2b89c415

This model is a fine-tuned version of HuggingFaceM4/tiny-random-LlamaForCausalLM 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: 4
total_train_batch_size: 8
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: 10
training_steps: 20

Training results

Training Loss	Epoch	Step	Validation Loss
10.3962	0.0001	1	nan
10.3918	0.0003	2	nan
10.3956	0.0006	4	nan
10.3797	0.0008	6	nan
10.3953	0.0011	8	nan
10.4019	0.0014	10	nan
10.4035	0.0017	12	nan
10.3903	0.0020	14	nan
10.3791	0.0023	16	nan
10.3808	0.0025	18	nan
10.3815	0.0028	20	nan

Framework versions

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