---
tags:
- Hopper-v5
- deep-reinforcement-learning
- reinforcement-learning
- custom-implementation
library_name: cleanrl
model-index:
- name: TD3
  results:
  - task:
      type: reinforcement-learning
      name: reinforcement-learning
    dataset:
      name: Hopper-v5
      type: Hopper-v5
    metrics:
    - type: mean_reward
      value: 1329.44 +/- 156.77
      name: mean_reward
      verified: false
---

# (CleanRL) **TD3** Agent Playing **Hopper-v5**

This is a trained model of a TD3 agent playing Hopper-v5.
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/td3.py).

## Get Started

To use this model, please install the `cleanrl` package with the following command:

```
pip install "cleanrl[td3]"
python -m cleanrl_utils.enjoy --exp-name td3 --env-id Hopper-v5
```

Please refer to the [documentation](https://docs.cleanrl.dev/get-started/zoo/) for more detail.


## Command to reproduce the training

```bash
curl -OL https://huggingface.co/jacksonhack/Hopper-v5-td3-seed1/raw/main/td3.py
curl -OL https://huggingface.co/jacksonhack/Hopper-v5-td3-seed1/raw/main/pyproject.toml
curl -OL https://huggingface.co/jacksonhack/Hopper-v5-td3-seed1/raw/main/poetry.lock
poetry install --all-extras
python td3.py --save_model --upload_model --track
```

# Hyperparameters
```python
{'batch_size': 256,
 'buffer_size': 1000000,
 'capture_video': False,
 'cuda': True,
 'env_id': 'Hopper-v5',
 'exp_name': 'td3',
 'exploration_noise': 0.1,
 'gamma': 0.99,
 'hf_entity': 'jacksonhack',
 'learning_rate': 0.0003,
 'learning_starts': 25000.0,
 'noise_clip': 0.5,
 'policy_frequency': 2,
 'policy_noise': 0.2,
 'save_model': True,
 'seed': 1,
 'tau': 0.005,
 'torch_deterministic': True,
 'total_timesteps': 1000000,
 'track': True,
 'upload_model': True,
 'wandb_entity': None,
 'wandb_project_name': 'cleanRL'}
```