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train-fine-tune – AI Model by Adzka | AlphaNeural AI
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Adzka
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train-fine-tune
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peft
tensorboard
safetensors
generated_from_trainer
aisingapore/SEA-LION-v1-7B-IT
adapter
mit
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train-fine-tune
This model is a fine-tuned version of
aisingapore/sea-lion-7b-instruct
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: QuantizationMethod.BITS_AND_BYTES
_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: fp4
bnb_4bit_use_double_quant: False
bnb_4bit_compute_dtype: float32
load_in_4bit: True
load_in_8bit: False
Training hyperparameters
The following hyperparameters were used during training:
learning_rate: 5e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5
mixed_precision_training: Native AMP
Training results
Framework versions
PEFT 0.5.0
Transformers 4.38.2
Pytorch 2.1.0+cu121
Datasets 2.14.5
Tokenizers 0.15.2
