Initial commit
Browse files- .gitattributes +1 -0
- README.md +86 -0
- args.yml +83 -0
- config.yml +29 -0
- dqn-SpaceInvadersNoFrameskip-v4.zip +3 -0
- dqn-SpaceInvadersNoFrameskip-v4/_stable_baselines3_version +1 -0
- dqn-SpaceInvadersNoFrameskip-v4/data +0 -0
- dqn-SpaceInvadersNoFrameskip-v4/policy.optimizer.pth +3 -0
- dqn-SpaceInvadersNoFrameskip-v4/policy.pth +3 -0
- dqn-SpaceInvadersNoFrameskip-v4/pytorch_variables.pth +3 -0
- dqn-SpaceInvadersNoFrameskip-v4/system_info.txt +9 -0
- env_kwargs.yml +1 -0
- replay.mp4 +0 -0
- results.json +1 -0
- train_eval_metrics.zip +3 -0
.gitattributes
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.mp4 filter=lfs diff=lfs merge=lfs -text
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README.md
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---
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library_name: stable-baselines3
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tags:
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- SpaceInvadersNoFrameskip-v4
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- deep-reinforcement-learning
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- reinforcement-learning
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- stable-baselines3
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model-index:
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- name: DQN
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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: SpaceInvadersNoFrameskip-v4
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type: SpaceInvadersNoFrameskip-v4
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metrics:
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- type: mean_reward
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value: 675.00 +/- 397.63
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name: mean_reward
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verified: false
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---
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# **DQN** Agent playing **SpaceInvadersNoFrameskip-v4**
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This is a trained model of a **DQN** agent playing **SpaceInvadersNoFrameskip-v4**
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using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
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and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
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The RL Zoo is a training framework for Stable Baselines3
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reinforcement learning agents,
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with hyperparameter optimization and pre-trained agents included.
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## Usage (with SB3 RL Zoo)
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RL Zoo: https://github.com/DLR-RM/rl-baselines3-zoo<br/>
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SB3: https://github.com/DLR-RM/stable-baselines3<br/>
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SB3 Contrib: https://github.com/Stable-Baselines-Team/stable-baselines3-contrib
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Install the RL Zoo (with SB3 and SB3-Contrib):
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```bash
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pip install rl_zoo3
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```
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```
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# Download model and save it into the logs/ folder
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python -m rl_zoo3.load_from_hub --algo dqn --env SpaceInvadersNoFrameskip-v4 -orga Tatsss -f logs/
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python -m rl_zoo3.enjoy --algo dqn --env SpaceInvadersNoFrameskip-v4 -f logs/
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```
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If you installed the RL Zoo3 via pip (`pip install rl_zoo3`), from anywhere you can do:
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```
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python -m rl_zoo3.load_from_hub --algo dqn --env SpaceInvadersNoFrameskip-v4 -orga Tatsss -f logs/
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python -m rl_zoo3.enjoy --algo dqn --env SpaceInvadersNoFrameskip-v4 -f logs/
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```
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## Training (with the RL Zoo)
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```
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python -m rl_zoo3.train --algo dqn --env SpaceInvadersNoFrameskip-v4 -f logs/
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# Upload the model and generate video (when possible)
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python -m rl_zoo3.push_to_hub --algo dqn --env SpaceInvadersNoFrameskip-v4 -f logs/ -orga Tatsss
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```
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## Hyperparameters
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```python
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OrderedDict([('batch_size', 32),
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('buffer_size', 100000),
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('env_wrapper',
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['stable_baselines3.common.atari_wrappers.AtariWrapper']),
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('exploration_final_eps', 0.01),
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('exploration_fraction', 0.1),
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('frame_stack', 4),
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('gradient_steps', 1),
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('learning_rate', 0.0001),
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('learning_starts', 100000),
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('n_timesteps', 1000000.0),
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('optimize_memory_usage', False),
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('policy', 'CnnPolicy'),
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('target_update_interval', 1000),
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('train_freq', 4),
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('normalize', False)])
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```
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# Environment Arguments
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```python
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{'render_mode': 'rgb_array'}
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```
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args.yml
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!!python/object/apply:collections.OrderedDict
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- - - algo
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- dqn
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- - conf_file
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- /dqn.yml
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- - device
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- auto
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- - env
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- SpaceInvadersNoFrameskip-v4
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- - env_kwargs
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- null
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- - eval_env_kwargs
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- null
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- - eval_episodes
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- 5
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- - eval_freq
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- 25000
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- - gym_packages
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- []
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- - hyperparams
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- null
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- - log_folder
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- logs/
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- - log_interval
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- -1
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- - max_total_trials
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- null
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- - n_eval_envs
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- 1
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- - n_evaluations
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- null
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- - n_jobs
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- 1
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- - n_startup_trials
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- 10
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- - n_timesteps
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- -1
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- - n_trials
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- 500
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- - no_optim_plots
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- false
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- - num_threads
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- -1
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- - optimization_log_path
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- null
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- - optimize_hyperparameters
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- false
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- - progress
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- false
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- - pruner
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- median
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- - sampler
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- tpe
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- - save_freq
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- -1
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- - save_replay_buffer
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- false
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- - seed
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- 1538624284
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- - storage
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- null
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- - study_name
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- null
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- - tensorboard_log
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- ''
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- - track
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- false
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- - trained_agent
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- ''
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- - truncate_last_trajectory
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- true
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- - uuid
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+
- false
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+
- - vec_env
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+
- dummy
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- - verbose
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- 1
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+
- - wandb_entity
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- null
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- - wandb_project_name
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- sb3
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- - wandb_tags
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- []
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config.yml
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!!python/object/apply:collections.OrderedDict
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- - - batch_size
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- 32
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- - buffer_size
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- 100000
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- - env_wrapper
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- - stable_baselines3.common.atari_wrappers.AtariWrapper
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8 |
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- - exploration_final_eps
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- 0.01
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+
- - exploration_fraction
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- 0.1
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- - frame_stack
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- 4
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- - gradient_steps
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- 1
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- - learning_rate
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- 0.0001
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- - learning_starts
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- 100000
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- - n_timesteps
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- 1000000.0
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- - optimize_memory_usage
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- false
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- - policy
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- CnnPolicy
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- - target_update_interval
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- 1000
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- - train_freq
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- 4
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dqn-SpaceInvadersNoFrameskip-v4.zip
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version https://git-lfs.github.com/spec/v1
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oid sha256:a4b91fc57e20a076803807b25955c22030f1ca041eaefdfc1fb9b11e3890bbe6
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size 27220644
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dqn-SpaceInvadersNoFrameskip-v4/_stable_baselines3_version
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2.4.0a7
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dqn-SpaceInvadersNoFrameskip-v4/data
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The diff for this file is too large to render.
See raw diff
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dqn-SpaceInvadersNoFrameskip-v4/policy.optimizer.pth
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version https://git-lfs.github.com/spec/v1
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+
oid sha256:6088972f6262aadd93fe9a2ecb0dd0edfb625adefd322ed0cff39e65b898801e
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size 13506172
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dqn-SpaceInvadersNoFrameskip-v4/policy.pth
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version https://git-lfs.github.com/spec/v1
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oid sha256:f4adf232c4a23e969751bad1abe11fc18dc8a453dd8ac722ee68745da1f7b6c1
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size 13505370
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dqn-SpaceInvadersNoFrameskip-v4/pytorch_variables.pth
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version https://git-lfs.github.com/spec/v1
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oid sha256:0c35cea3b2e60fb5e7e162d3592df775cd400e575a31c72f359fb9e654ab00c5
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size 864
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dqn-SpaceInvadersNoFrameskip-v4/system_info.txt
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- OS: Linux-6.1.85+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Thu Jun 27 21:05:47 UTC 2024
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- Python: 3.10.12
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- Stable-Baselines3: 2.4.0a7
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- PyTorch: 2.4.1+cu121
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- GPU Enabled: True
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- Numpy: 1.26.4
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- Cloudpickle: 3.1.0
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- Gymnasium: 0.29.1
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- OpenAI Gym: 0.25.2
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env_kwargs.yml
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render_mode: rgb_array
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replay.mp4
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Binary file (256 kB). View file
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results.json
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{"mean_reward": 675.0, "std_reward": 397.63048172895395, "is_deterministic": false, "n_eval_episodes": 10, "eval_datetime": "2024-10-22T16:27:37.325695"}
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train_eval_metrics.zip
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version https://git-lfs.github.com/spec/v1
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+
oid sha256:f12bc670c4a72548e95bbc8a203de628aa52de9ecc3ef37e7fab91608054446a
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size 36296
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