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@@ -93,17 +93,6 @@ output_text = processor.batch_decode(
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  print(output_text)
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  ```
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- ## Training Details
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-
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- | Parameter | Value |
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- |-------------------------|-----------------------------------------------------|
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- | **Dataset Size** | 108K samples (Modular Combustion of Datasets) |
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- | **Model Architecture** | `Qwen2_5_VLForConditionalGeneration` |
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- | **Total Disk Volume** | 300,000 MB |
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- | **Training Time** | approx. 12,897 seconds (~3.58 hours) |
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- | **Warmup Steps** | 750 |
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- | **Precision** | bfloat16 |
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-
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  # Intended Use
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  This model is intended for:
@@ -126,6 +115,16 @@ This model is intended for:
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  * Visual token settings affect performance; suboptimal configurations can impact results.
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  * In rare cases, outputs may contain hallucinated or contextually misaligned information.
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  ## References
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  print(output_text)
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  ```
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  # Intended Use
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  This model is intended for:
 
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  * Visual token settings affect performance; suboptimal configurations can impact results.
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  * In rare cases, outputs may contain hallucinated or contextually misaligned information.
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+ ## Training Details
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+
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+ | Parameter | Value |
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+ |-------------------------|-----------------------------------------------------|
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+ | **Dataset Size** | 108K samples (Modular Combustion of Datasets) |
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+ | **Model Architecture** | `Qwen2_5_VLForConditionalGeneration` |
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+ | **Total Disk Volume** | 300,000 MB |
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+ | **Training Time** | approx. 12,897 seconds (~3.58 hours) |
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+ | **Warmup Steps** | 750 |
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+ | **Precision** | bfloat16 |
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  ## References
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