Instructions to use PengxinWang/RobustLLMAgent with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use PengxinWang/RobustLLMAgent with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
Add qwen2_5_1_5_stable_gaussian_noise_v9_step_200_seed0 step200 LoRA adapter and run config
#4
by Davidk1 - opened
- results/webshop/robust_training/qwen2_5_1_5_stable_gaussian_noise_v9_step_200_seed0/checkpoints/global_step_200/actor/lora_adapter/adapter_config.json +51 -0
- results/webshop/robust_training/qwen2_5_1_5_stable_gaussian_noise_v9_step_200_seed0/checkpoints/global_step_200/actor/lora_adapter/adapter_model.safetensors +3 -0
- results/webshop/robust_training/qwen2_5_1_5_stable_gaussian_noise_v9_step_200_seed0/logs/tensorboard/events.out.tfevents.1790134325.train8.3168242.0 +3 -0
- results/webshop/robust_training/qwen2_5_1_5_stable_gaussian_noise_v9_step_200_seed0/logs/tensorboard/events.out.tfevents.1790146713.train8.3292090.0 +3 -0
- results/webshop/robust_training/qwen2_5_1_5_stable_gaussian_noise_v9_step_200_seed0/run_config.json +276 -0
results/webshop/robust_training/qwen2_5_1_5_stable_gaussian_noise_v9_step_200_seed0/checkpoints/global_step_200/actor/lora_adapter/adapter_config.json
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{
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"task_type": "CAUSAL_LM",
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"peft_type": "LORA",
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"auto_mapping": null,
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| 5 |
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"peft_version": "0.19.1",
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"base_model_name_or_path": "/home/yuxinr/.cache/huggingface/hub/models--Qwen--Qwen2.5-1.5B-Instruct/snapshots/989aa7980e4cf806f80c7fef2b1adb7bc71aa306",
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"revision": null,
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"inference_mode": false,
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"r": 64,
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"target_modules": [
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"down_proj",
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"gate_proj",
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"k_proj",
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"o_proj",
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"q_proj",
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"up_proj",
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"v_proj"
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],
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"exclude_modules": null,
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"lora_alpha": 64,
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"lora_dropout": 0.0,
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"fan_in_fan_out": false,
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"bias": "none",
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"use_rslora": false,
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"modules_to_save": null,
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"init_lora_weights": true,
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"layers_to_transform": null,
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"layers_pattern": null,
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"rank_pattern": {},
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"alpha_pattern": {},
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"megatron_config": null,
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"megatron_core": "megatron.core",
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"trainable_token_indices": null,
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"loftq_config": {},
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"eva_config": null,
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"corda_config": null,
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"lora_ga_config": null,
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"use_dora": false,
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"alora_invocation_tokens": null,
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"use_qalora": false,
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"qalora_group_size": 16,
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"layer_replication": null,
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"runtime_config": {
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"ephemeral_gpu_offload": false
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},
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"lora_bias": false,
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| 47 |
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"target_parameters": null,
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| 48 |
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"use_bdlora": null,
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"arrow_config": null,
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"ensure_weight_tying": false
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}
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results/webshop/robust_training/qwen2_5_1_5_stable_gaussian_noise_v9_step_200_seed0/checkpoints/global_step_200/actor/lora_adapter/adapter_model.safetensors
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version https://git-lfs.github.com/spec/v1
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size 295488904
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results/webshop/robust_training/qwen2_5_1_5_stable_gaussian_noise_v9_step_200_seed0/logs/tensorboard/events.out.tfevents.1790134325.train8.3168242.0
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version https://git-lfs.github.com/spec/v1
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size 38386
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results/webshop/robust_training/qwen2_5_1_5_stable_gaussian_noise_v9_step_200_seed0/logs/tensorboard/events.out.tfevents.1790146713.train8.3292090.0
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version https://git-lfs.github.com/spec/v1
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size 1898681
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results/webshop/robust_training/qwen2_5_1_5_stable_gaussian_noise_v9_step_200_seed0/run_config.json
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| 1 |
+
{
|
| 2 |
+
"base_model": "989aa7980e4cf806f80c7fef2b1adb7bc71aa306",
|
| 3 |
+
"environment": "webshop",
|
| 4 |
+
"experiment_name": "qwen2_5_1_5_stable_gaussian_noise_v9_step_200_seed0",
|
| 5 |
+
"implementation_sha256": {
|
| 6 |
+
"scripts/train/clean/run_webshop_1expert_1k_tmux.sh": "505c382630dd089246d8cf7f2101254c932f762338f86291e52118c7eb0d7785",
|
| 7 |
+
"scripts/train/robust/gaussian/run_training.sh": "3c6e237d1a6d27f01d8aef836ae591f1644c4806abefbef27ed453cdfa0c0c8e",
|
| 8 |
+
"verl/models/adaptive_ffn_channel_noise.py": "9b5865cbb6142e06a97f20677369dfe50a885641882231f241b1d48f115f9249",
|
| 9 |
+
"verl/trainer/config/ppo_trainer.yaml": "f0b5654b0bbdf585bad56259942301121d5d694d4bf94aca3f459dd3a6d292e6",
|
| 10 |
+
"verl/workers/actor/dp_actor.py": "fbaa9cb65975acf52404db4443119118419804098fc6d1e18c7b9417e82ea1b8"
|
| 11 |
+
},
|
| 12 |
+
"model_path": "/home/yuxinr/.cache/huggingface/hub/models--Qwen--Qwen2.5-1.5B-Instruct/snapshots/989aa7980e4cf806f80c7fef2b1adb7bc71aa306",
|
| 13 |
+
"perturbation": {
|
| 14 |
+
"actor_weights_perturbed": false,
|
| 15 |
+
"channel_ema_symbol": "lambda_EMA",
|
| 16 |
+
"checkpoint_state_file": "adaptive_ffn_noise.pt",
|
| 17 |
+
"distribution": "multiplicative_normal_scale_1_plus_channel_std_times_epsilon",
|
| 18 |
+
"empty_response_sensitivity_contribution": 0.0,
|
| 19 |
+
"extra_actor_backward_passes_per_rollout_batch": 1,
|
| 20 |
+
"extra_environment_rollouts_per_step": 0,
|
| 21 |
+
"extra_forward_backward_beyond_existing_sensitivity_prepass": 0,
|
| 22 |
+
"family": "stable_gaussian_noise",
|
| 23 |
+
"global_scale_estimator": "squared_L2_norm_of_full_batch_mean_PPO_parameter_gradient_from_sensitivity_prepass",
|
| 24 |
+
"global_scale_used_for": "next_global_step_noise_standard_deviation_only",
|
| 25 |
+
"global_std_cap_after_warmup": 0.4,
|
| 26 |
+
"global_std_cap_multiplier": 2.0,
|
| 27 |
+
"global_std_formula": "sigma_base * warmup * min(updated_policy_full_batch_mean_gradient_squared, clip_multiplier)",
|
| 28 |
+
"global_weight_clipping": true,
|
| 29 |
+
"global_weight_ema": false,
|
| 30 |
+
"gradient_source": "clipped_PPO_policy_objective_only_with_GiGPO_advantages",
|
| 31 |
+
"initial_variance_allocation": "isotropic_before_first_sensitivity_estimate",
|
| 32 |
+
"outer_gradient": "PPO_loss_of_perturbed_policy_on_its_noisy_rollout_against_noisy_vllm_behavior_log_probs_with_identical_channel_scale",
|
| 33 |
+
"rollout_fixed_scale_path_at_engine_initialization": "/home/yuxinr/yuanzhe/RobustLLMAgent/results/webshop/robust_training/qwen2_5_1_5_stable_gaussian_noise_v9_step_200_seed0/logs/adaptive_rollout_clean_scale.pt",
|
| 34 |
+
"rollout_perturbation": true,
|
| 35 |
+
"rollout_scale_path": "/home/yuxinr/yuanzhe/RobustLLMAgent/results/webshop/robust_training/qwen2_5_1_5_stable_gaussian_noise_v9_step_200_seed0/logs/adaptive_rollout_scale.pt",
|
| 36 |
+
"rollout_sigma": 0.2,
|
| 37 |
+
"rollout_sigma_schedule": "warmup_times_base_sigma_times_clipped_post_update_gradient_squared",
|
| 38 |
+
"sampling_mode": "step",
|
| 39 |
+
"scope": "one_per_layer_channel_vector_shared_by_all_rollouts_and_actor_mini_batches_in_one_global_step",
|
| 40 |
+
"sensitivity_estimator": "mean_over_rollout_rows_of_squared_channel_gain_gradient_of_sequence_mean_policy_loss",
|
| 41 |
+
"sensitivity_is_fisher": false,
|
| 42 |
+
"sensitivity_normalization": "per_layer_mean_before_EMA",
|
| 43 |
+
"sensitivity_prepass": "updated_noisy_policy_over_entire_existing_rollout_batch_after_all_optimizer_updates",
|
| 44 |
+
"sensitivity_used_for": "next_global_step_variance_only; current_rollout_and_PPO_scale_remains_frozen",
|
| 45 |
+
"settings": {
|
| 46 |
+
"allow_schedule_override": false,
|
| 47 |
+
"alpha": 0.0,
|
| 48 |
+
"damping": 0.01,
|
| 49 |
+
"ema_decay": 0.9,
|
| 50 |
+
"enabled": true,
|
| 51 |
+
"global_scale_clip_multiplier": 2.0,
|
| 52 |
+
"global_scale_fixed_multiplier": -1.0,
|
| 53 |
+
"global_scale_floor": 0.0,
|
| 54 |
+
"global_scale_mode": "prepass_grad_squared",
|
| 55 |
+
"initial_global_scale": 1.0,
|
| 56 |
+
"max_variance_ratio": 4.0,
|
| 57 |
+
"min_variance_ratio": 0.25,
|
| 58 |
+
"seed": 0,
|
| 59 |
+
"sigma": 0.2,
|
| 60 |
+
"statistics_timing": "post_update",
|
| 61 |
+
"warmup_steps": 20
|
| 62 |
+
},
|
| 63 |
+
"statistics_gradient_clipped": false,
|
| 64 |
+
"statistics_timing": "post_update",
|
| 65 |
+
"stop_gradient": [
|
| 66 |
+
"sensitivity",
|
| 67 |
+
"EMA",
|
| 68 |
+
"variance",
|
| 69 |
+
"sampled_channel_noise"
|
| 70 |
+
],
|
| 71 |
+
"type": "adaptive_gaussian_ffn_channel_noise",
|
| 72 |
+
"update_mode": "lagged_rollout_adaptive",
|
| 73 |
+
"validation_clean_scale_path": "/home/yuxinr/yuanzhe/RobustLLMAgent/results/webshop/robust_training/qwen2_5_1_5_stable_gaussian_noise_v9_step_200_seed0/logs/adaptive_rollout_clean_scale.pt",
|
| 74 |
+
"validation_perturbation": false,
|
| 75 |
+
"variance_allocation": "inverse_damped_EMA_sensitivity_power_alpha_with_bounded_unit_layer_mean_variance_ratios",
|
| 76 |
+
"variance_projection": "scalar_rescale_with_bounds_and_exact_layer_mean_ratio_1",
|
| 77 |
+
"variance_weight_formula": "(layer_normalized_EMA_sensitivity+damping)^(-alpha)",
|
| 78 |
+
"warmup_formula": "sigma*min((completed_adaptive_updates+1)/warmup_steps,1); full_sigma_when_warmup_steps_is_0"
|
| 79 |
+
},
|
| 80 |
+
"result_category": "robust_training",
|
| 81 |
+
"resume_history": [
|
| 82 |
+
{
|
| 83 |
+
"architecture": "x86_64",
|
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