Cosine_matric_llama2_prompt1 – AI Model by Bakugo123 | AlphaNeural AI

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Cosine_matric_llama2_prompt1

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NousResearch/Llama-2-7b-chat-hf

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Cosine_matric_llama2_prompt1

This model is a fine-tuned version of NousResearch/Llama-2-7b-chat-hf on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.9479

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: False
bnb_4bit_compute_dtype: float16
load_in_4bit: True
load_in_8bit: False

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 0.0002
train_batch_size: 4
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: constant
lr_scheduler_warmup_ratio: 0.05
num_epochs: 2
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
1.0276	0.4	384	0.9479
1.0277	0.8	768	0.9479
1.0213	1.2	1152	0.9479
1.0277	1.6	1536	0.9479
0.8449	2.0	1920	0.9479

Framework versions

PEFT 0.4.0
Transformers 4.38.2
Pytorch 2.1.2
Datasets 2.1.0
Tokenizers 0.15.2