Upload . with huggingface_hub
Browse files- .gitattributes +2 -0
- .summary/0/events.out.tfevents.1677255776.B450Mint +3 -0
- .summary/0/events.out.tfevents.1677266685.B450Mint +3 -0
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- README.md +56 -0
- checkpoint_p0/best_000057775_236646400_reward_62.094.pth +3 -0
- checkpoint_p0/checkpoint_000060807_249065472.pth +3 -0
- checkpoint_p0/checkpoint_000061037_250007552.pth +3 -0
- config.json +142 -0
- replay.mp4 +3 -0
- sf_log.txt +3 -0
.gitattributes
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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sf_log.txt filter=lfs diff=lfs merge=lfs -text
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replay.mp4 filter=lfs diff=lfs merge=lfs -text
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.summary/0/events.out.tfevents.1677255776.B450Mint
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README.md
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---
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library_name: sample-factory
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tags:
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- deep-reinforcement-learning
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- reinforcement-learning
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- sample-factory
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model-index:
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- name: APPO
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results:
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- task:
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type: reinforcement-learning
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name: reinforcement-learning
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dataset:
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name: doom_deathmatch_bots
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type: doom_deathmatch_bots
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metrics:
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- type: mean_reward
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value: 52.10 +/- 8.26
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name: mean_reward
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verified: false
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---
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A(n) **APPO** model trained on the **doom_deathmatch_bots** environment.
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This model was trained using Sample-Factory 2.0: https://github.com/alex-petrenko/sample-factory.
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Documentation for how to use Sample-Factory can be found at https://www.samplefactory.dev/
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## Downloading the model
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After installing Sample-Factory, download the model with:
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```
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python -m sample_factory.huggingface.load_from_hub -r besa2001/rl_course_vizdoom_doom_deathmatch_bots
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```
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## Using the model
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To run the model after download, use the `enjoy` script corresponding to this environment:
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```
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python -m <path.to.enjoy.module> --algo=APPO --env=doom_deathmatch_bots --train_dir=./train_dir --experiment=rl_course_vizdoom_doom_deathmatch_bots
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```
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You can also upload models to the Hugging Face Hub using the same script with the `--push_to_hub` flag.
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See https://www.samplefactory.dev/10-huggingface/huggingface/ for more details
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## Training with this model
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To continue training with this model, use the `train` script corresponding to this environment:
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```
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python -m <path.to.train.module> --algo=APPO --env=doom_deathmatch_bots --train_dir=./train_dir --experiment=rl_course_vizdoom_doom_deathmatch_bots --restart_behavior=resume --train_for_env_steps=10000000000
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```
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Note, you may have to adjust `--train_for_env_steps` to a suitably high number as the experiment will resume at the number of steps it concluded at.
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checkpoint_p0/best_000057775_236646400_reward_62.094.pth
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size 35139491
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checkpoint_p0/checkpoint_000060807_249065472.pth
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checkpoint_p0/checkpoint_000061037_250007552.pth
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version https://git-lfs.github.com/spec/v1
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config.json
ADDED
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{
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"help": false,
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3 |
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"algo": "APPO",
|
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"env": "doom_deathmatch_bots",
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5 |
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"experiment": "default_experiment",
|
6 |
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"train_dir": "/home/besa/source/rl/train_dir",
|
7 |
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"restart_behavior": "resume",
|
8 |
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"device": "gpu",
|
9 |
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"seed": null,
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"num_policies": 1,
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"async_rl": true,
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"serial_mode": false,
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"batched_sampling": false,
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"num_batches_to_accumulate": 2,
|
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"worker_num_splits": 2,
|
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"policy_workers_per_policy": 1,
|
17 |
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"max_policy_lag": 1000,
|
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"num_workers": 8,
|
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"num_envs_per_worker": 4,
|
20 |
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"batch_size": 1024,
|
21 |
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"num_batches_per_epoch": 1,
|
22 |
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"num_epochs": 1,
|
23 |
+
"rollout": 32,
|
24 |
+
"recurrence": 32,
|
25 |
+
"shuffle_minibatches": false,
|
26 |
+
"gamma": 0.99,
|
27 |
+
"reward_scale": 1.0,
|
28 |
+
"reward_clip": 1000.0,
|
29 |
+
"value_bootstrap": false,
|
30 |
+
"normalize_returns": true,
|
31 |
+
"exploration_loss_coeff": 0.001,
|
32 |
+
"value_loss_coeff": 0.5,
|
33 |
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"kl_loss_coeff": 0.0,
|
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"exploration_loss": "symmetric_kl",
|
35 |
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"gae_lambda": 0.95,
|
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"ppo_clip_ratio": 0.1,
|
37 |
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"ppo_clip_value": 0.2,
|
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"with_vtrace": false,
|
39 |
+
"vtrace_rho": 1.0,
|
40 |
+
"vtrace_c": 1.0,
|
41 |
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"optimizer": "adam",
|
42 |
+
"adam_eps": 1e-06,
|
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"adam_beta1": 0.9,
|
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"adam_beta2": 0.999,
|
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"max_grad_norm": 4.0,
|
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"learning_rate": 0.0001,
|
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"lr_schedule": "constant",
|
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"lr_schedule_kl_threshold": 0.008,
|
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"lr_adaptive_min": 1e-06,
|
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"lr_adaptive_max": 0.01,
|
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"obs_subtract_mean": 0.0,
|
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"obs_scale": 255.0,
|
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"normalize_input": true,
|
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"normalize_input_keys": null,
|
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"decorrelate_experience_max_seconds": 0,
|
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"decorrelate_envs_on_one_worker": true,
|
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"actor_worker_gpus": [],
|
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"set_workers_cpu_affinity": true,
|
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"force_envs_single_thread": false,
|
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"default_niceness": 0,
|
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"log_to_file": true,
|
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"experiment_summaries_interval": 10,
|
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"flush_summaries_interval": 30,
|
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"stats_avg": 100,
|
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"summaries_use_frameskip": true,
|
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"heartbeat_interval": 20,
|
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"heartbeat_reporting_interval": 600,
|
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"train_for_env_steps": 250000000,
|
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"train_for_seconds": 10000000000,
|
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"save_every_sec": 120,
|
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"keep_checkpoints": 2,
|
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"load_checkpoint_kind": "latest",
|
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"save_milestones_sec": -1,
|
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"save_best_every_sec": 5,
|
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"save_best_metric": "reward",
|
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"save_best_after": 100000,
|
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"benchmark": false,
|
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"encoder_mlp_layers": [
|
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512,
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512
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],
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"encoder_conv_architecture": "convnet_simple",
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"encoder_conv_mlp_layers": [
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512
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],
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"use_rnn": true,
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"rnn_size": 512,
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"rnn_type": "gru",
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"rnn_num_layers": 1,
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"decoder_mlp_layers": [],
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"nonlinearity": "elu",
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"policy_initialization": "orthogonal",
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"policy_init_gain": 1.0,
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"actor_critic_share_weights": true,
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"adaptive_stddev": true,
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"continuous_tanh_scale": 0.0,
|
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"initial_stddev": 1.0,
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"use_env_info_cache": false,
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"env_gpu_actions": false,
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"env_gpu_observations": true,
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"env_frameskip": 4,
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"env_framestack": 1,
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"pixel_format": "CHW",
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"use_record_episode_statistics": false,
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"with_wandb": false,
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"wandb_user": null,
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"wandb_project": "sample_factory",
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"wandb_group": null,
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"wandb_job_type": "SF",
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"wandb_tags": [],
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"with_pbt": false,
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"pbt_mix_policies_in_one_env": true,
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"pbt_period_env_steps": 5000000,
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"pbt_start_mutation": 20000000,
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"pbt_replace_fraction": 0.3,
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"fps": 35,
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"command_line": "--env=doom_deathmatch_bots --num_workers=8 --num_envs_per_worker=4 --train_for_env_steps=100000000",
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"cli_args": {
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"env": "doom_deathmatch_bots",
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"num_workers": 8,
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"num_envs_per_worker": 4,
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"train_for_env_steps": 100000000
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},
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"git_hash": "unknown",
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"git_repo_name": "not a git repository"
|
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}
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replay.mp4
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