File size: 1,768 Bytes
a6507cb |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 |
---
tags:
- CartPole-v1
- deep-reinforcement-learning
- reinforcement-learning
- custom-implementation
library_name: cleanrl
model-index:
- name: C51
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: CartPole-v1
type: CartPole-v1
metrics:
- type: mean_reward
value: 500.00 +/- 0.00
name: mean_reward
verified: false
---
# (CleanRL) **C51** Agent Playing **CartPole-v1**
This is a trained model of a C51 agent playing CartPole-v1.
The model was trained by using [CleanRL](https://github.com/vwxyzjn/cleanrl) and the most up-to-date training code can be
found [here](https://github.com/vwxyzjn/cleanrl/blob/master/cleanrl/c51.py).
## Command to reproduce the training
```bash
curl -OL https://huggingface.co/cleanrl/CartPole-v1-c51-seed1/raw/main/c51.py
curl -OL https://huggingface.co/cleanrl/CartPole-v1-c51-seed1/raw/main/pyproject.toml
curl -OL https://huggingface.co/cleanrl/CartPole-v1-c51-seed1/raw/main/poetry.lock
poetry install --all-extras
python c51.py --save-model --upload-model --hf-entity cleanrl --cuda False --env-id CartPole-v1
```
# Hyperparameters
```python
{'batch_size': 128,
'buffer_size': 10000,
'capture_video': False,
'cuda': False,
'end_e': 0.05,
'env_id': 'CartPole-v1',
'exp_name': 'c51',
'exploration_fraction': 0.5,
'gamma': 0.99,
'hf_entity': 'cleanrl',
'learning_rate': 0.00025,
'learning_starts': 10000,
'n_atoms': 101,
'save_model': True,
'seed': 1,
'start_e': 1,
'target_network_frequency': 500,
'torch_deterministic': True,
'total_timesteps': 500000,
'track': False,
'train_frequency': 10,
'upload_model': True,
'v_max': 100,
'v_min': -100,
'wandb_entity': None,
'wandb_project_name': 'cleanRL'}
```
|