docs(card): use Gemma 4 VL SFT recipe defaults

Signed-off-by: yaoyu-33 <yaoyu.094@gmail.com>

Author: yaoyu-33

examples/model_verification_cards/gemma-4-26b-a4b-it/card.yaml

@@ -182,26 +182,23 @@ items:
       status: verified
       precision: bf16
       enabled_features: {}
-      bridge_commit: 07d182e7e8df4421e445906b29e6b5f4a2f4a6f1  # pragma: allowlist secret
+      bridge_commit: f3130a0e37c78945ecf98b301dfc90505c3c305f  # pragma: allowlist secret
       command: >
         ./scripts/training/train.sh --nodes 1 --gpus-per-node 8
         --recipe gemma4_vl_26b_sft_config --mode sft --dataset cord-v2
         --pretrained_checkpoint work/model-verification/gemma-4-26b-a4b-it/imported-megatron/iter_0000000
         --max_steps 10 --seq_length 4096
         'dataset.source.load_kwargs={revision:"7f0115a4b758a71d6473b8d085751692da2fef98"}'
         validation.eval_iters=0 validation.eval_interval=0 checkpoint.load=null
-        model.recompute_granularity=full model.recompute_modules=null
-        model.recompute_method=uniform model.recompute_num_layers=1
-        model.cuda_graph_impl=none
         --save_dir work/model-verification/gemma-4-26b-a4b-it/sft-checkpoints
         --save_interval 10 logger.log_interval=1 logger.log_throughput=true
         logger.save_config_filepath=work/model-verification/gemma-4-26b-a4b-it/sft-post-setup.yaml
       last_verified: 2026-08-11
       metrics:
         initial_loss: 1.282612
-        final_loss: 0.07524271
-        last_10_steps_step_time_ms_avg: 15600.68
-        last_10_steps_model_tflops_per_gpu_avg: 32.95
+        final_loss: 0.09127883
+        last_10_steps_step_time_ms_avg: 15936.25
+        last_10_steps_model_tflops_per_gpu_avg: 32.20
         peak_allocated_memory_gib: 65.223
         peak_reserved_memory_gib: 72.356
       expected_result: >
@@ -210,10 +207,11 @@ items:
         optimizer steps at MBS1 and GBS32. The persisted post-setup config
         confirmed a frozen vision encoder, trainable projection and language
         model, expandable CUDA allocator segments, and full-layer uniform
-        recompute with one layer per recompute unit while CUDA graphs and CPU
-        offload remained disabled. Loss moved from 1.282612 to 0.07524271,
-        final grad norm was 2.094, and every step reported zero skipped and zero
-        NaN iterations. After iteration 2, logger-reported ranks returned to
+        recompute with one layer per recompute unit directly from the recipe
+        defaults, while CUDA graphs and CPU offload remained disabled. Loss
+        moved from 1.282612 to 0.09127883, final grad norm was 3.090, and all 10
+        steps reported zero skipped and zero NaN iterations. After iteration 2,
+        logger-reported ranks returned to
         62.134-62.145 GiB allocated, while cumulative peak allocated and
         reserved memory remained at or below 65.223 and 72.356 GiB. The run
         saved a complete iter_0000010 torch_dist checkpoint with eight rank