diff --git a/training/README.md b/training/README.md
index 62225b6e..135e23d1 100644
--- a/training/README.md
+++ b/training/README.md
@@ -30,8 +30,7 @@ pip install -e .
 5. Install vLLM:
 
 ```bash
-pip install -U vllm --pre --extra-index-url https://wheels.vllm.ai/nightly
-
+pip install vllm==0.6.3
 ```
 6. Install flash attention
 ```
diff --git a/training/configs/qwen2.5_3b_grpo.yaml b/training/configs/qwen2.5_3b_grpo.yaml
index a279e85d..00d6837d 100644
--- a/training/configs/qwen2.5_3b_grpo.yaml
+++ b/training/configs/qwen2.5_3b_grpo.yaml
@@ -1,20 +1,27 @@
 reasoning_gym:
   dataset_size: 20000
   developer_prompt: DeepSeekZero
-  datasets:
-    spell_backward:
-        weight: 1
-        config:
-          min_word_len: 3
-          max_word_len: 10
+  datasets:  # Used if enable_curriculum_learning is False
+    mini_sudoku:
+      weight: 0.33
+      config:
+        min_empty: 6
+    futoshiki:
+      weight: 0.33
+      config:
+        max_board_size: 5
+    sudoku:
+      weight: 0.34
+      config:
+        min_empty: 20
 curriculum:
     enabled: False
     schedule:
       automatic: True
       update_steps: 30 # automatic curriculum updating after 50 steps
     last_k: 20
-    success_threshold: 0.7
-    failure_threshold: 0.1
+    success_threshold: 0.70
+    failure_threshold: 0.10
     curricula:
       spell_backward:
         attribute_levels:
@@ -31,12 +38,11 @@ data:
   val_files: test.parquet
   prompt_key: prompt
   max_prompt_length: 512
-  max_response_length: 1024
-  train_batch_size: 32
-  val_batch_size: 32
+  max_response_length: 2048
+  train_batch_size: 16
+  val_batch_size: 16
   return_raw_chat: True
   return_raw_input_ids: True
-
 actor_rollout_ref:
   hybrid_engine: True
   model:
@@ -47,11 +53,11 @@ actor_rollout_ref:
     use_remove_padding: True
   actor:
     strategy: fsdp  # This is for backward-compatibility
-    ppo_mini_batch_size: 32
+    ppo_mini_batch_size: 16
     ppo_micro_batch_size: null # will be deprecated, use ppo_micro_batch_size_per_gpu
     ppo_micro_batch_size_per_gpu: 8
     use_dynamic_bsz: False
-    ppo_max_token_len_per_gpu: 12288 # n * ${data.max_prompt_length} + ${data.max_response_length}
+    ppo_max_token_len_per_gpu: 20480 # n * ${data.max_prompt_length} + ${data.max_response_length}
     grad_clip: 1.0
     clip_ratio: 0.2
     entropy_coeff: 0.001
@@ -63,9 +69,9 @@ actor_rollout_ref:
     ulysses_sequence_parallel_size: 1 # sp size
     optim:
       lr: 1e-6
-      lr_warmup_steps_ratio: 0  # the total steps will be injected during runtime
+      lr_warmup_steps_ratio: 0.  # the total steps will be injected during runtime
       min_lr_ratio: null   # only useful for warmup with cosine
-      warmup_style: constant # select from constant/cosine
+      warmup_style: constant  # select from constant/cosine
       total_training_steps: -1  # must be override by program
     fsdp_config:
       wrap_policy:
@@ -99,7 +105,7 @@ actor_rollout_ref:
     enforce_eager: True
     free_cache_engine: True
     load_format: dummy_dtensor
-    tensor_model_parallel_size: 4
+    tensor_model_parallel_size: 2
     max_num_batched_tokens: 16384
     max_num_seqs: 1024
     log_prob_micro_batch_size: null # will be deprecated, use log_prob_micro_batch_size_per_gpu
@@ -128,14 +134,14 @@ algorithm:
 verbose: True
 trainer:
   balance_batch: True
-  total_epochs: 5
+  total_epochs: 10
   total_training_steps: null
   project_name: rg-test
-  experiment_name: verl_grpo_qwen_composite
+  experiment_name: verl_grpo_qwen_3b
   logger: [ 'console', 'wandb' ]
   val_generations_to_log_to_wandb: 0
   nnodes: 1
-  n_gpus_per_node: 4
+  n_gpus_per_node: 2
   save_freq: 100
   # auto: find the last ckpt to resume. If can't find, start from scratch
   resume_mode: auto # or auto or resume_path if
@@ -147,13 +153,14 @@ trainer:
   del_local_ckpt_after_load: False
   default_local_dir: checkpoints/${trainer.project_name}/${trainer.experiment_name}
 
+
 critic:
   strategy: fsdp
   optim:
-    lr: 1e-6
-    lr_warmup_steps_ratio: 0  # the total steps will be injected during runtime
+    lr: 1e-5
+    lr_warmup_steps_ratio: 0.  # the total steps will be injected during runtime
     min_lr_ratio: null   # only useful for warmup with cosine
-    warmup_style: cosine  # select from constant/cosine
+    warmup_style: constant  # select from constant/cosine
     total_training_steps: -1  # must be override by program
   model:
     path: ~/models/deepseek-llm-7b-chat