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alchemist69/
72a4ea13-9c48-4267-b34f-ffbfa5d40d8e

Name: 72a4ea13-9c48-4267-b34f-ffbfa5d40d8e
Availability: InStock

generated_from_trainer

defog/llama-3-sqlcoder-8b

adapter

cc-by-sa-4.0

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See axolotl config

axolotl version: 0.4.1

yaml

adapter: lora
base_model: defog/llama-3-sqlcoder-8b
bf16: true
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
  - 4d3ccfd148a48951_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/4d3ccfd148a48951_train_data.json
  type:
    field_instruction: question
    field_output: positive_answer
    format: '{instruction}'
    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: true
fp16: false
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 4
gradient_checkpointing: true
group_by_length: true
hub_model_id: alchemist69/72a4ea13-9c48-4267-b34f-ffbfa5d40d8e
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/4d3ccfd148a48951_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 1
optim_args:
  adam_beta1: 0.9
  adam_beta2: 0.95
  adam_epsilon: 1e-5
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
special_tokens:
  pad_token: <|eot_id|>
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: fbae069e-fb6e-483d-98a1-0b88f4497a85
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: fbae069e-fb6e-483d-98a1-0b88f4497a85
warmup_steps: 10
weight_decay: 0.0
xformers_attention: null

72a4ea13-9c48-4267-b34f-ffbfa5d40d8e

This model is a fine-tuned version of defog/llama-3-sqlcoder-8b on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.7102

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-5
lr_scheduler_type: cosine
lr_scheduler_warmup_steps: 10
training_steps: 349

Training results

Training Loss	Epoch	Step	Validation Loss
1.0583	0.0029	1	1.3076
1.0381	0.1433	50	0.9951
1.1454	0.2865	100	0.8978
1.0357	0.4298	150	0.8184
0.8913	0.5731	200	0.7626
0.9414	0.7163	250	0.7297
0.971	0.8596	300	0.7102

Framework versions

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