resume-summarizer – AI Model by npnik4 | AlphaNeural AI

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npnik4/
resume-summarizer

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text-generation

npnik4/resume_and_summary

autotrain_compatible

text-generation-inference

endpoints_compatible

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Training procedure

The following bitsandbytes quantization config was used during training:

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

Framework versions

PEFT 0.4.0

The following hyperparameters were used during training:

train_batch_size: 2
eval_batch_size: 2
num_epochs: 10

Step	Training Loss
25	2.124
50	1.835
75	1.657
100	1.403
125	1.113