See axolotl config

axolotl version: 0.4.1

adapter: lora
base_model: fxmarty/really-tiny-falcon-testing
bf16: true
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
  - 8eb1b0c596068a27_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/8eb1b0c596068a27_train_data.json
  type:
    field_input: input
    field_instruction: question
    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: 5
eval_batch_size: 4
eval_max_new_tokens: 128
eval_steps: 50
eval_table_size: null
evals_per_epoch: null
flash_attention: false
fp16: false
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 4
gradient_checkpointing: true
group_by_length: true
hub_model_id: auxyus/ab898c80-419a-406a-bc0d-be1faab9607f
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: 128
lora_dropout: 0.05
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 64
lora_target_linear: true
lr_scheduler: cosine
max_grad_norm: 1.0
max_memory:
  0: 75GB
max_steps: 400
micro_batch_size: 8
mlflow_experiment_name: /tmp/8eb1b0c596068a27_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_bnb_8bit
output_dir: miner_id_24
pad_to_sequence_len: true
resume_from_checkpoint: null
s2_attention: null
sample_packing: false
save_steps: 50
saves_per_epoch: null
sequence_len: 1024
strict: false
tf32: true
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.05
wandb_entity: techspear-hub
wandb_mode: online
wandb_name: 7dfae140-8291-48f1-be29-ad30bbaa9933
wandb_project: Gradients-On-Two
wandb_run: your_name
wandb_runid: 7dfae140-8291-48f1-be29-ad30bbaa9933
warmup_steps: 10
weight_decay: 0.0
xformers_attention: null

ab898c80-419a-406a-bc0d-be1faab9607f

This model is a fine-tuned version of fxmarty/really-tiny-falcon-testing on the None dataset. It achieves the following results on the evaluation set:

• Loss: 10.7877

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: 8
• eval_batch_size: 4
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 32
• 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-05
• lr_scheduler_type: cosine
• lr_scheduler_warmup_steps: 10
• training_steps: 400

Training results

Training Loss	Epoch	Step	Validation Loss
44.3387	0.0035	1	11.0888
43.2215	0.1773	50	10.8634
42.9994	0.3546	100	10.8191
43.0289	0.5319	150	10.8042
42.9546	0.7092	200	10.7959
42.8736	0.8865	250	10.7926
43.2787	1.0638	300	10.7879
43.2293	1.2411	350	10.7873
43.2214	1.4184	400	10.7877

Framework versions

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