Beta
Explore
Marketplace
Neural Labs
Chat
Wallet
Docs
continual-pretraining-checkpoint – AI Model by Bachhoang | AlphaNeural AI
You can deploy this model and start earning money today!
Bachhoang
/
continual-pretraining-checkpoint
like
0
peft
safetensors
generated_from_trainer
Bachhoang/vbd-llama2-7B-legals-chat
adapter
us
Views
No views yet
Model card
Files and Versions
Community
API
Deploy
continual-pretraining-checkpoint
This model is a fine-tuned version of
Bachhoang/vbd-llama2-7B-legals-chat
on an unknown dataset.
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
The following
bitsandbytes
quantization config was used during training:
quant_method: bitsandbytes
_load_in_8bit: False
_load_in_4bit: True
llm_int8_threshold: 6.0
llm_int8_skip_modules: None
llm_int8_enable_fp32_cpu_offload: False
llm_int8_has_fp16_weight: False
bnb_4bit_quant_type: nf4
bnb_4bit_use_double_quant: True
bnb_4bit_compute_dtype: float16
bnb_4bit_quant_storage: uint8
load_in_4bit: True
load_in_8bit: False
Training hyperparameters
The following hyperparameters were used during training:
learning_rate: 0.0002
train_batch_size: 1
eval_batch_size: 1
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 2
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_steps: 2
num_epochs: 1
mixed_precision_training: Native AMP
Framework versions
PEFT 0.5.0
Transformers 4.39.3
Pytorch 2.1.2
Datasets 2.16.0
Tokenizers 0.15.2
