README.md

---
library_name: stable-baselines3
tags:
- PandaReachDense-v3
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: A2C
  results:
  - task:
      type: reinforcement-learning
      name: reinforcement-learning
    dataset:
      name: PandaReachDense-v3
      type: PandaReachDense-v3
    metrics:
    - type: mean_reward
      value: -0.20 +/- 0.09
      name: mean_reward
      verified: false
---

# **A2C** Agent playing **PandaReachDense-v3**
This is a trained model of a **A2C** agent playing **PandaReachDense-v3**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).

## Usage (with Stable-baselines3)

```python
from stable_baselines3 import A2C
from huggingface_sb3 import load_from_hub

model = load_from_hub(repo_id='Francesco-A/a2c-PandaReachDense-v3',
                     filename= 'a2c-PandaReachDense-v3.zip')
```

## Training details (last output)


Metric               | Value  
---------------------|--------
rollout/ep_len_mean  | 4.05   
rollout/ep_rew_mean  | -0.317 
time/fps             | 378    
time/iterations      | 50000  
time/time_elapsed    | 2641   
time/total_timesteps | 1000000
train/entropy_loss   | 1.25   
train/explained_variance | 0.975
train/learning_rate  | 0.0007 
train/n_updates      | 49999  
train/policy_loss    | -0.0935
train/std            | 0.185  
train/value_loss     | 0.0306