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romainnn/
a6b81d7a-635d-4e60-8c88-11261e5e688e

Name: a6b81d7a-635d-4e60-8c88-11261e5e688e
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:
  - cde84cb3aee56411_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/cde84cb3aee56411_train_data.json
  type:
    field_input: reasoning
    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: 2
early_stopping_threshold: 0.0001
eval_max_new_tokens: 128
eval_steps: 100
eval_table_size: null
flash_attention: false
fp16: null
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 8
gradient_checkpointing: true
group_by_length: false
hub_model_card: false
hub_model_id: romainnn/a6b81d7a-635d-4e60-8c88-11261e5e688e
hub_repo: null
hub_strategy: checkpoint
hub_token: null
learning_rate: 0.0002
load_best_model_at_end: true
load_in_4bit: false
load_in_8bit: false
local_rank: null
logging_steps: 1
lora_alpha: 128
lora_dropout: 0.3
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 64
lora_target_linear: true
lora_target_modules:
- q_proj
- k_proj
- v_proj
lr_scheduler: cosine
max_grad_norm: 1.0
max_steps: 632
micro_batch_size: 4
mlflow_experiment_name: /tmp/cde84cb3aee56411_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 2
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: 2048
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: a2e48d24-f6a8-4e6d-bbb1-2b0d36f9e6bc
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: a2e48d24-f6a8-4e6d-bbb1-2b0d36f9e6bc
warmup_steps: 10
weight_decay: 0.0
xformers_attention: null

a6b81d7a-635d-4e60-8c88-11261e5e688e

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: 0.4517

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: 4
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 32
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: 632

Training results

Training Loss	Epoch	Step	Validation Loss
6.6887	0.0011	1	0.7235
4.0459	0.1140	100	0.5077
3.3402	0.2279	200	0.4868
3.8981	0.3419	300	0.4731
4.0368	0.4558	400	0.4617
3.7167	0.5698	500	0.4539
4.1802	0.6838	600	0.4517

Framework versions

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