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regional_perception_checkpoint-6379/README.md

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+---
+base_model: /data1/wjx/model/InternVL2-26B
+library_name: peft
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.11.1

regional_perception_checkpoint-6379/adapter_config.json

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+  "base_model_name_or_path": "/data1/wjx/model/InternVL2-26B",
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+  "target_modules": [
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+    "w1",
+    "proj",
+    "mlp1.3",
+    "fc1",
+    "w3",
+    "output",
+    "mlp1.1"
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+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}

regional_perception_checkpoint-6379/adapter_model.safetensors

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regional_perception_checkpoint-6379/additional_config.json

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regional_perception_checkpoint-6379/configuration.json

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+{
+    "adapter_cfg": {
+        "model_id_or_path": "/data1/wjx/model/InternVL2-26B",
+        "model_revision": "master",
+        "sft_type": "lora",
+        "tuner_backend": "peft",
+        "template_type": "internvl2",
+        "dtype": "bf16",
+        "system": "You are a seasoned driver, skilled at handling corner cases."
+    }
+}

regional_perception_checkpoint-6379/generation_config.json

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+{
+  "do_sample": true,
+  "eos_token_id": 2,
+  "max_new_tokens": 2048,
+  "pad_token_id": 2,
+  "temperature": 0.3,
+  "top_k": 20,
+  "top_p": 0.7,
+  "transformers_version": "4.37.2"
+}

regional_perception_checkpoint-6379/optimizer.pt

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regional_perception_checkpoint-6379/rng_state.pth

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regional_perception_checkpoint-6379/scheduler.pt

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regional_perception_checkpoint-6379/sft_args.json

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+{
+  "model_type": "internvl2-26b",
+  "model_id_or_path": "/data1/wjx/model/InternVL2-26B",
+  "model_revision": "master",
+  "sft_type": "lora",
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+  "additional_trainable_parameters": [],
+  "tuner_backend": "peft",
+  "template_type": "internvl2",
+  "output_dir": "/data1/wjx/model/swift/output/v1d+v3_prompt/output/internvl2-26b/v0-20240810-170945",
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+  "resume_from_checkpoint": null,
+  "resume_only_model": false,
+  "ignore_data_skip": false,
+  "dtype": "bf16",
+  "packing": false,
+  "dataset": [
+    "/data1/wjx/date/CODA/CODA-LM/Train/vqa_anno/train_v1d+v3_region_perception_for_swfit.jsonl",
+    "/data1/wjx/date/CODA/CODA-LM/Val/vqa_anno/val_v1d+v3_region_perception_for_swfit.jsonl"
+  ],
+  "val_dataset": [
+    "/data1/wjx/date/CODA/CODA-LM/Mini/vqa_anno/mini_v1d+v3_region_perception_for_swfit.jsonl"
+  ],
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+  "dataset_test_ratio": 0.0,
+  "use_loss_scale": false,
+  "loss_scale_config_path": "/data1/wjx/model/swift/swift/llm/agent/default_loss_scale_config.json",
+  "system": "You are a seasoned driver, skilled at handling corner cases.",
+  "tools_prompt": "react_en",
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+  "truncation_strategy": "delete",
+  "check_dataset_strategy": "none",
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+}

regional_perception_checkpoint-6379/training_args.bin

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