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tm-hf-0/
a29763ea-08d6-4330-abb6-3ddb8ded7246

Name: a29763ea-08d6-4330-abb6-3ddb8ded7246
Availability: InStock

generated_from_trainer

NousResearch/Meta-Llama-3-8B

adapter

other

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See axolotl config

axolotl version: 0.4.1

yaml

adapter: lora
base_model: NousResearch/Meta-Llama-3-8B
bf16: auto
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
  - 07160dc26b76d0f9_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/07160dc26b76d0f9_train_data.json
  type:
    field_input: description
    field_instruction: title
    field_output: prompt
    format: '{instruction} {input}'
    no_input_format: '{instruction}'
    system_format: '{system}'
    system_prompt: ''
debug: null
deepspeed: null
early_stopping_patience: 1
eval_max_new_tokens: 64
eval_steps: 100
eval_table_size: null
flash_attention: true
fp16: null
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 4
gradient_checkpointing: true
group_by_length: false
hub_model_id: tm-hf-0/a29763ea-08d6-4330-abb6-3ddb8ded7246
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: 8
lora_target_linear: true
lr_scheduler: cosine
micro_batch_size: 4
mlflow_experiment_name: /tmp/07160dc26b76d0f9_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 30
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: 100
sequence_len: 512
special_tokens:
  pad_token: <|end_of_text|>
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: e2f3571e-c29b-40e9-be11-c010b9776a98
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: e2f3571e-c29b-40e9-be11-c010b9776a98
warmup_steps: 100
weight_decay: 0.01
xformers_attention: null

a29763ea-08d6-4330-abb6-3ddb8ded7246

This model is a fine-tuned version of NousResearch/Meta-Llama-3-8B on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.0001

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: 4
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: 100
num_epochs: 30

Training results

Training Loss	Epoch	Step	Validation Loss
2.366	0.0005	1	2.3671
0.0	0.0489	100	0.0013
0.0032	0.0979	200	0.0003
0.0	0.1468	300	0.0002
0.0015	0.1957	400	0.0001
0.0	0.2446	500	0.0001
0.0	0.2936	600	0.0001
0.0	0.3425	700	0.0001

Framework versions

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