A deep neural network that learns to drive in video games
GPL-3.0 License
Published by ikergarcia1996 almost 2 years ago
T.E.D.D. 1104 S: 138M Parameters. 1.6GB
control_mode: keyboard
cnn_model_name: efficientnet_v2_l
pretrained_cnn: true
encoder_type: transformer
embedded_size: 896
nhead: 8
num_layers_encoder: 4
learning_rate: 1e-05
optimizer_name: adafactor
scheduler_name: cosine
warmup_factor: 0.05
max_epochs: 20
batch_size: 32
mask_prob: 0.2
dropout_cnn_out: 0.3
dropout_encoder: 0.1
dropout_encoder_features: 0.3
positional_embeddings_dropout: 0.1
weight_decay: 1e-3
Accuracy in the test datasets:
Time | Weather | Micro-Acc K@1 | Micro-Acc k@3 | Macro-Acc K@1 | |
---|---|---|---|---|---|
City | 🌞 | ☀️ | 53.2 | 84.4 | 46.2 |
City | 🌞 | ☔ | 51.4 | 83.4 | 46.3 |
City | 🌛 | ☀️ | 54.3 | 85.6 | 46.3 |
City | 🌛 | ☔ | 47.3 | 82.3 | 49.9 |
Highway | 🌞 | ☀️ | 72.7 | 97.7 | 40.6 |
Highway | 🌞 | ☔ | 70.6 | 99.3 | 39.6 |
Highway | 🌛 | ☀️ | 77.9 | 99.3 | 45.7 |
Highway | 🌛 | ☔ | 70.9 | 97.6 | 30.8 |
The release includes the best epoch in the development set and the last epoch.
Published by ikergarcia1996 almost 2 years ago
T.E.D.D. 1104 S: 68M Parameters. 685MB
control_mode: keyboard
cnn_model_name: efficientnet_v2_m
pretrained_cnn: true
encoder_type: transformer
embedded_size: 512
nhead: 8
num_layers_encoder: 4
learning_rate: 1e-05
optimizer_name: adafactor
scheduler_name: cosine
warmup_factor: 0.05
max_epochs: 20
batch_size: 32
mask_prob: 0.2
dropout_cnn_out: 0.3
dropout_encoder: 0.1
dropout_encoder_features: 0.3
positional_embeddings_dropout: 0.1
weight_decay: 1e-3
Accuracy in the test datasets:
Time | Weather | Micro-Acc K@1 | Micro-Acc k@3 | Macro-Acc K@1 | |
---|---|---|---|---|---|
City | 🌞 | ☀️ | 52.9 | 84.1 | 43.1 |
City | 🌞 | ☔ | 49.9 | 81.3 | 42.2 |
City | 🌛 | ☀️ | 54.7 | 85.1 | 48.4 |
City | 🌛 | ☔ | 49.5 | 81.1 | 41.1 |
Highway | 🌞 | ☀️ | 62.5 | 99.2 | 43.1 |
Highway | 🌞 | ☔ | 71.9 | 99.3 | 39.2 |
Highway | 🌛 | ☀️ | 79.4 | 99.3 | 45.3 |
Highway | 🌛 | ☔ | 63.0 | 97.2 | 47.2 |
The release includes the best epoch in the development set and the last epoch.
Published by ikergarcia1996 almost 2 years ago
T.E.D.D. 1104 S: 26M Parameters. 260MB
control_mode: keyboard
cnn_model_name: efficientnet_v2_s
pretrained_cnn: true
encoder_type: transformer
embedded_size: 384
nhead: 8
num_layers_encoder: 2
learning_rate: 1e-05
optimizer_name: adafactor
scheduler_name: cosine
warmup_factor: 0.05
max_epochs: 20
batch_size: 32
mask_prob: 0.2
dropout_cnn_out: 0.3
dropout_encoder: 0.1
dropout_encoder_features: 0.3
positional_embeddings_dropout: 0.1
weight_decay: 1e-3
Accuracy in the test datasets:
Time | Weather | Micro-Acc K@1 | Micro-Acc k@3 | Macro-Acc K@1 | |
---|---|---|---|---|---|
City | 🌞 | ☀️ | 51.0 | 83.0 | 46.3 |
City | 🌞 | ☔ | 49.0 | 82.5 | 45.2 |
City | 🌛 | ☀️ | 56.3 | 86.6 | 49.0 |
City | 🌛 | ☔ | 49.4 | 81.4 | 42.5 |
Highway | 🌞 | ☀️ | 70.3 | 100 | 68.5 |
Highway | 🌞 | ☔ | 71.2 | 100 | 37.6 |
Highway | 🌛 | ☀️ | 80.9 | 100 | 49.1 |
Highway | 🌛 | ☔ | 69.3 | 100 | 61.1 |
The release includes the best epoch in the development set and the last epoch.
Published by ikergarcia1996 over 2 years ago
THIS MODEL WILL NOT WORK WITH THE CURRENT VERSION OF TEDD1104
T.E.D.D. 1104 Base: 34.6M Parameters. 415.9Mb
cnn_model_name: efficientnet_b4
control_mode: keyboard
dropout_cnn_out: 0.3
dropout_encoder: 0.1
dropout_encoder_features: 0.3
embedded_size: 512
encoder_type: transformer
learning_rate: 1.0e-05
lstm_hidden_size: 512
mask_prob: 0.2
nhead: 8
num_layers_encoder: 4
positional_embeddings_dropout: 0.1
pretrained_cnn: true
sequence_size: 5
weight_decay: 0.001
weights: null
num_epochs: 12
batch_size: 64
Time | Weather | Micro-Acc K@1 | Micro-Acc k@3 | Macro-Acc K@1 | |
---|---|---|---|---|---|
City | 🌞 | ☀️ | 49.8 | 83.8 | 44.1 |
City | 🌞 | ☔ | 52.1 | 84.7 | 46.1 |
City | 🌛 | ☀️ | 54.5 | 86.9 | 48.0 |
City | 🌛 | ☔ | 48.8 | 82.5 | 43.2 |
Highway | 🌞 | ☀️ | 65.6 | 100.0 | 53.2 |
Highway | 🌞 | ☔ | 70.6 | 98.0 | 54.2 |
Highway | 🌛 | ☀️ | 71.3 | 100.0 | 52.3 |
Highway | 🌛 | ☔ | 67.7 | 100.0 | 50.9 |