Model save

README.md

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+---
+base_model: google/paligemma-3b-pt-224
+library_name: peft
+license: gemma
+tags:
+- generated_from_trainer
+model-index:
+- name: paligemma_scienceQA_v15
+  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. -->
+
+# paligemma_scienceQA_v15
+
+This model is a fine-tuned version of [google/paligemma-3b-pt-224](https://huggingface.co/google/paligemma-3b-pt-224) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- eval_loss: 0.1162
+- eval_runtime: 61.0128
+- eval_samples_per_second: 1.328
+- eval_steps_per_second: 0.672
+- epoch: 4.0
+- step: 200
+
+## Model description
+
+More information needed
+
+## 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: 1e-05
+- train_batch_size: 2
+- eval_batch_size: 2
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 8
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 10
+
+### Framework versions
+
+- PEFT 0.12.0
+- Transformers 4.43.3
+- Pytorch 2.3.1+cu121
+- Datasets 2.20.0
+- Tokenizers 0.19.1

config.json

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+    "projection_dim": 2048,
+    "hidden_size": 2048,
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+        "pruned_heads": {},
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+        "early_stopping": false,
+        "num_beams": 1,
+        "num_beam_groups": 1,
+        "diversity_penalty": 0.0,
+        "temperature": 1.0,
+        "top_k": 50,
+        "top_p": 1.0,
+        "typical_p": 1.0,
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+        "_name_or_path": "",
+        "model_type": "siglip_vision_model",
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+        "projection_dim": 2048,
+        "projector_hidden_act": "gelu_fast",
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+        "hidden_size": 1152,
+        "intermediate_size": 4304,
+        "num_hidden_layers": 27,
+        "num_attention_heads": 16,
+        "num_channels": 3,
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+        "attention_dropout": 0.0,
+        "layer_norm_eps": 1e-06,
+        "hidden_act": "gelu_pytorch_tanh"
+    },
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+    "text_config": {
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+        "max_position_embeddings": 8192,
+        "hidden_size": 2048,
+        "intermediate_size": 16384,
+        "num_hidden_layers": 18,
+        "num_attention_heads": 8,
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+        "num_key_value_heads": 1,
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+    "transformers_version": "4.43.3",
+    "model_type": "paligemma",
+    "quantization_config": {
+        "quant_method": "bitsandbytes",
+        "_load_in_8bit": false,
+        "_load_in_4bit": true,
+        "llm_int8_threshold": 6.0,
+        "llm_int8_skip_modules": null,
+        "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": "bfloat16",
+        "bnb_4bit_quant_storage": "uint8",
+        "load_in_4bit": true,
+        "load_in_8bit": false
+    }
+}

preprocessor_config.json

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+{"chat_template": null, "processor_class": "PaliGemmaProcessor"}