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eddysang/
abf304b8-4e9d-49c1-ba1d-6636bf0237f6

Name: abf304b8-4e9d-49c1-ba1d-6636bf0237f6
Availability: InStock

generated_from_trainer

custom_code

NousResearch/Yarn-Llama-2-7b-128k

adapter

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See axolotl config

axolotl version: 0.4.1

yaml

adapter: lora
base_model: NousResearch/Yarn-Llama-2-7b-128k
bf16: true
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
  - e8a169737f717450_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/e8a169737f717450_train_data.json
  type:
    field_input: input
    field_instruction: instruction
    field_output: output
    format: '{instruction} {input}'
    no_input_format: '{instruction}'
    system_format: '{system}'
    system_prompt: ''
debug: null
deepspeed: null
early_stopping_patience: null
eval_max_new_tokens: 256
eval_table_size: null
evals_per_epoch: 4
flash_attention: false
fp16: null
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 32
gradient_checkpointing: true
group_by_length: false
hub_model_id: eddysang/abf304b8-4e9d-49c1-ba1d-6636bf0237f6
hub_repo: null
hub_strategy: checkpoint
hub_token: null
learning_rate: 0.00015
load_in_4bit: false
load_in_8bit: false
local_rank: null
logging_steps: 3
lora_alpha: 64
lora_dropout: 0.05
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 32
lora_target_linear: true
lora_target_modules:
- q_proj
- k_proj
- v_proj
- o_proj
lr_scheduler: cosine
max_grad_norm: 2
max_steps: 100
micro_batch_size: 2
mlflow_experiment_name: /tmp/e8a169737f717450_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 3
optim_args:
  adam_beta1: 0.9
  adam_beta2: 0.95
  adam_epsilon: 1.0e-05
optimizer: adamw_torch
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: 2048
strict: false
tf32: false
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.05
wandb_entity: yaudayah0
wandb_mode: online
wandb_name: b9218a5c-d101-43de-8ece-e20c6eb9134c
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: b9218a5c-d101-43de-8ece-e20c6eb9134c
warmup_steps: 20
weight_decay: 0.02
xformers_attention: false

abf304b8-4e9d-49c1-ba1d-6636bf0237f6

This model is a fine-tuned version of NousResearch/Yarn-Llama-2-7b-128k on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.5928

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: 0.00015
train_batch_size: 2
eval_batch_size: 2
seed: 42
gradient_accumulation_steps: 32
total_train_batch_size: 64
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=adam_beta1=0.9,adam_beta2=0.95,adam_epsilon=1e-05
lr_scheduler_type: cosine
lr_scheduler_warmup_steps: 20
training_steps: 100

Training results

Training Loss	Epoch	Step	Validation Loss
No log	0.0002	1	1.0045
29.6533	0.0022	9	0.8682
23.219	0.0045	18	0.7282
21.3012	0.0067	27	0.6667
20.2279	0.0090	36	0.6394
21.057	0.0112	45	0.6244
18.6364	0.0135	54	0.6130
18.0383	0.0157	63	0.6046
19.8381	0.0180	72	0.5989
18.3124	0.0202	81	0.5951
18.3766	0.0225	90	0.5933
18.9632	0.0247	99	0.5928

Framework versions

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