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README.md

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+Quantization made by Richard Erkhov.
+
+[Github](https://github.com/RichardErkhov)
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+[Request more models](https://github.com/RichardErkhov/quant_request)
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+
+Phi-3.5-vision-instruct_20240915_223241 - AWQ
+- Model creator: https://huggingface.co/muhtasham/
+- Original model: https://huggingface.co/muhtasham/Phi-3.5-vision-instruct_20240915_223241/
+
+
+
+
+Original model description:
+---
+library_name: transformers
+license: mit
+base_model: microsoft/Phi-3.5-vision-instruct
+tags:
+- generated_from_trainer
+model-index:
+- name: Phi-3.5-vision-instruct_20240915_223241
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# Phi-3.5-vision-instruct_20240915_223241
+
+This model is a fine-tuned version of [microsoft/Phi-3.5-vision-instruct](https://huggingface.co/microsoft/Phi-3.5-vision-instruct) on the None dataset.
+
+## Model description
+
+On 1.8M avg dataset
+
+## 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: 4e-05
+- train_batch_size: 1
+- eval_batch_size: 1
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 8
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 16
+- total_eval_batch_size: 8
+- optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-07
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 50
+- num_epochs: 4
+- mixed_precision_training: Native AMP
+
+### Training results
+
+
+
+### Framework versions
+
+- Transformers 4.44.2
+- Pytorch 2.4.1+cu121
+- Datasets 3.0.0
+- Tokenizers 0.19.1
+
+