metadata
library_name: peft
license: cc-by-sa-4.0
base_model: defog/llama-3-sqlcoder-8b
tags:
- axolotl
- generated_from_trainer
model-index:
- name: c0fa4d77-a9c9-46e1-a9d1-b5956ab43c5d
results: []
See axolotl config
axolotl version: 0.4.1
adapter: lora
base_model: defog/llama-3-sqlcoder-8b
bf16: auto
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
- 7e29722059d9d568_train_data.json
ds_type: json
format: custom
path: /workspace/input_data/7e29722059d9d568_train_data.json
type:
field_instruction: Speech
field_output: Speech_processed
format: '{instruction}'
no_input_format: '{instruction}'
system_format: '{system}'
system_prompt: ''
debug: null
deepspeed: null
device: cuda
early_stopping_patience: 1
eval_max_new_tokens: 128
eval_steps: 5
eval_table_size: null
evals_per_epoch: null
flash_attention: false
fp16: null
gradient_accumulation_steps: 4
gradient_checkpointing: true
gradient_clipping: 1.0
group_by_length: true
hub_model_id: infogep/c0fa4d77-a9c9-46e1-a9d1-b5956ab43c5d
hub_repo: null
hub_strategy: checkpoint
hub_token: null
learning_rate: 5.0e-05
load_in_4bit: false
load_in_8bit: false
local_rank: null
logging_steps: 3
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
max_steps: 30
micro_batch_size: 4
mlflow_experiment_name: /tmp/7e29722059d9d568_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 1
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: 10
sequence_len: 1024
special_tokens:
pad_token: <|eot_id|>
strict: false
tf32: false
tokenizer_type: AutoTokenizer
train_on_inputs: true
trust_remote_code: true
val_set_size: 0.05
wandb_entity: null
wandb_mode: online
wandb_name: 3020def7-32ef-493e-ba2a-56aeb67fbd87
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: 3020def7-32ef-493e-ba2a-56aeb67fbd87
warmup_steps: 5
weight_decay: 0.0
xformers_attention: true
c0fa4d77-a9c9-46e1-a9d1-b5956ab43c5d
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: 1.8507
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: 5e-05
- 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: 5
- training_steps: 30
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
No log | 0.0001 | 1 | 2.2399 |
1.4587 | 0.0005 | 5 | 2.2229 |
1.5717 | 0.0009 | 10 | 2.1020 |
1.5247 | 0.0014 | 15 | 1.9905 |
1.5183 | 0.0019 | 20 | 1.9088 |
1.5404 | 0.0023 | 25 | 1.8610 |
1.7174 | 0.0028 | 30 | 1.8507 |
Framework versions
- PEFT 0.13.2
- Transformers 4.46.0
- Pytorch 2.5.0+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1