See axolotl config
axolotl version: 0.4.0
base_model: NousResearch/Llama-2-7b-hf
model_type: LlamaForCausalLM
tokenizer_type: LlamaTokenizer
load_in_8bit: false
load_in_4bit: true
strict: false
datasets:
- path: caffeinatedcherrychic/cidds-agg-balanced
type: alpaca
dataset_prepared_path: last_run_prepared
val_set_size: 0.1
output_dir: ./qlora-out
adapter: qlora
lora_model_dir:
sequence_len: 2048
sample_packing: false
pad_to_sequence_len: true
lora_r: 32
lora_alpha: 64
lora_dropout: 0.05
lora_target_linear: true
lora_fan_in_fan_out:
lora_target_modules:
- gate_proj
- down_proj
- up_proj
- q_proj
- v_proj
- k_proj
- o_proj
wandb_project:
wandb_entity:
wandb_watch:
wandb_name:
wandb_log_model:
gradient_accumulation_steps: 4
micro_batch_size: 2
num_epochs: 5
optimizer: adamw_bnb_8bit
lr_scheduler: cosine
learning_rate: 0.0002
train_on_inputs: false
group_by_length: false
bf16: true
fp16: false
tf32: false
gradient_checkpointing: true
early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true
loss_watchdog_threshold: 5.0
loss_watchdog_patience: 3
max_steps: 500
warmup_steps: 10
evals_per_epoch: 4
eval_table_size:
eval_max_new_tokens: 1
saves_per_epoch: 1
debug:
deepspeed:
weight_decay: 0.001
fsdp:
fsdp_config:
special_tokens:
qlora-out
This model is a fine-tuned version of NousResearch/Llama-2-7b-hf on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1998
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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- training_steps: 62
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 6.6299 | 0.08 | 1 | 6.9320 |
| 5.9686 | 0.32 | 4 | 4.4463 |
| 0.5956 | 0.64 | 8 | 0.5577 |
| 0.4848 | 0.96 | 12 | 0.8370 |
| 0.4913 | 1.28 | 16 | 0.4896 |
| 0.671 | 1.6 | 20 | 0.5175 |
| 2.6136 | 1.92 | 24 | 2.3446 |
| 0.6383 | 2.24 | 28 | 0.5194 |
| 0.5776 | 2.56 | 32 | 0.5653 |
| 0.4913 | 2.88 | 36 | 0.4791 |
| 0.3486 | 3.2 | 40 | 0.4041 |
| 0.4944 | 3.52 | 44 | 0.3174 |
| 0.4788 | 3.84 | 48 | 0.3952 |
| 0.3321 | 4.16 | 52 | 0.2342 |
| 0.207 | 4.48 | 56 | 0.2058 |
| 0.4502 | 4.8 | 60 | 0.1998 |
Framework versions
- PEFT 0.10.1.dev0
- Transformers 4.39.0.dev0
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.0
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Model tree for caffeinatedcherrychic/Llama2-based-NIDS
Base model
NousResearch/Llama-2-7b-hf