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nttx/
43ee977a-6448-4ea0-9523-9594c7a0143f

Name: 43ee977a-6448-4ea0-9523-9594c7a0143f
Availability: InStock

generated_from_trainer

HuggingFaceH4/zephyr-7b-beta

adapter

mit

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See axolotl config

axolotl version: 0.4.1

yaml

adapter: lora
base_model: HuggingFaceH4/zephyr-7b-beta
bf16: true
chat_template: llama3
dataloader_num_workers: 24
dataset_prepared_path: null
datasets:
- data_files:
  - 70bd2504f9403a5d_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/70bd2504f9403a5d_train_data.json
  type:
    field_input: all_generated_responses
    field_instruction: prompt
    field_output: prompt_id
    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: 3
eval_batch_size: 2
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: 8
gradient_checkpointing: false
group_by_length: true
hub_model_id: nttx/43ee977a-6448-4ea0-9523-9594c7a0143f
hub_repo: null
hub_strategy: checkpoint
hub_token: null
learning_rate: 0.0002
load_in_4bit: false
load_in_8bit: false
local_rank: null
logging_steps: 50
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: 3000
micro_batch_size: 2
mlflow_experiment_name: /tmp/70bd2504f9403a5d_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 10
optim_args:
  adam_beta1: 0.9
  adam_beta2: 0.999
  adam_epsilon: 1e-8
optimizer: adamw_torch_fused
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
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: e1e965fc-c3b9-4969-b645-af01fc9a10e7
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: e1e965fc-c3b9-4969-b645-af01fc9a10e7
warmup_steps: 50
weight_decay: 0.0
xformers_attention: null

43ee977a-6448-4ea0-9523-9594c7a0143f

This model is a fine-tuned version of HuggingFaceH4/zephyr-7b-beta on the None dataset. It achieves the following results on the evaluation set:

Loss: 3.1636

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: 0.0002
train_batch_size: 2
eval_batch_size: 2
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 16
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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: 3000

Training results

Training Loss	Epoch	Step	Validation Loss
No log	0.0003	1	3.4447
24.3183	0.0405	150	3.0583
24.3103	0.0810	300	3.0725
24.4332	0.1214	450	3.0960
25.0763	0.1619	600	3.1636

Framework versions

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