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nttx/
a5ee2937-69a6-4426-996f-5aa17987c810

Name: a5ee2937-69a6-4426-996f-5aa17987c810
Availability: InStock

generated_from_trainer

EleutherAI/pythia-70m-deduped

adapter

apache-2.0

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See axolotl config

axolotl version: 0.4.1

yaml

adapter: lora
base_model: EleutherAI/pythia-70m-deduped
bf16: auto
chat_template: llama3
dataloader_num_workers: 12
dataset_prepared_path: null
datasets:
- data_files:
  - 5a568bfc958f4385_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/5a568bfc958f4385_train_data.json
  type:
    field_input: orig_response
    field_instruction: instruction
    field_output: output
    format: '{instruction} {input}'
    no_input_format: '{instruction}'
    system_format: '{system}'
    system_prompt: ''
debug: null
deepspeed: null
device_map: auto
do_eval: true
early_stopping_patience: 2
eval_batch_size: 4
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: 4
gradient_checkpointing: true
group_by_length: true
hub_model_id: nttx/a5ee2937-69a6-4426-996f-5aa17987c810
hub_repo: null
hub_strategy: end
hub_token: null
learning_rate: 5.0e-05
load_in_4bit: false
load_in_8bit: false
local_rank: null
logging_steps: 10
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_grad_norm: 1.0
max_memory:
  0: 75GB
max_steps: 900
micro_batch_size: 4
mlflow_experiment_name: /tmp/5a568bfc958f4385_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 10
optim_args:
  adam_beta1: 0.9
  adam_beta2: 0.95
  adam_epsilon: 1e-5
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: 150
saves_per_epoch: null
sequence_len: 512
special_tokens:
  pad_token: <|endoftext|>
strict: false
tf32: true
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.05
wandb_entity: null
wandb_mode: online
wandb_name: e29108f4-d366-4632-bee1-91f4584ab380
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: e29108f4-d366-4632-bee1-91f4584ab380
warmup_steps: 50
weight_decay: 0.0
xformers_attention: null

a5ee2937-69a6-4426-996f-5aa17987c810

This model is a fine-tuned version of EleutherAI/pythia-70m-deduped on the None dataset. It achieves the following results on the evaluation set:

Loss: 4.8074

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: 5e-05
train_batch_size: 4
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 16
optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=adam_beta1=0.9,adam_beta2=0.95,adam_epsilon=1e-5
lr_scheduler_type: cosine
lr_scheduler_warmup_steps: 50
training_steps: 900

Training results

Training Loss	Epoch	Step	Validation Loss
No log	0.0001	1	12.4252
22.5635	0.0169	150	5.4802
19.7155	0.0337	300	4.9590
19.2023	0.0506	450	4.8739
19.0622	0.0674	600	4.8344
18.8558	0.0843	750	4.8139
18.7662	0.1011	900	4.8074

Framework versions

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