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/venv/myenv/lib/python3.11/site-packages/pydantic/_internal/_generate_schema.py:2274: UnsupportedFieldAttributeWarning: The 'repr' attribute with value False was provided to the `Field()` function, which has no effect in the context it was used. 'repr' is field-specific metadata, and can only be attached to a model fie...
warnings.warn(
/venv/myenv/lib/python3.11/site-packages/pydantic/_internal/_generate_schema.py:2274: UnsupportedFieldAttributeWarning: The 'frozen' attribute with value True was provided to the `Field()` function, which has no effect in the context it was used. 'frozen' is field-specific metadata, and can only be attached to a model ...
warnings.warn(
Running experiment with seed 1...
Namespace(cuda=0, n_experiences=5, drop1=0.3, drop2=0.5, patience=10, eval_every=5, epochs=100, batch_size=64, init_lr=0.05, min_lr=0.001, seed=1, plugin='gnr', alpha=0.3, r=0.02, project_name='TAI-baselines-C5', run_name='gnr seed_1')
Emptying CUDA cache...
Files already downloaded and verified
Files already downloaded and verified
Starting training with seed 1.
-- >> Start of training phase << --
-- >> Start of eval phase << --
-- Starting eval on experience 0 (Task 0) from test stream --
0it [00:00, ?it/s]
3%|β–Ž | 1/32 [00:00<00:05, 5.48it/s]
3%|β–Ž | 1/32 [00:00<00:05, 5.48it/s]
6%|β–‹ | 2/32 [00:00<00:05, 5.48it/s]
9%|β–‰ | 3/32 [00:00<00:05, 5.48it/s]
12%|β–ˆβ–Ž | 4/32 [00:00<00:05, 5.48it/s]
16%|β–ˆβ–Œ | 5/32 [00:00<00:04, 5.48it/s]
19%|β–ˆβ–‰ | 6/32 [00:00<00:04, 5.48it/s]
22%|β–ˆβ–ˆβ– | 7/32 [00:00<00:04, 5.48it/s]
25%|β–ˆβ–ˆβ–Œ | 8/32 [00:00<00:04, 5.48it/s]
28%|β–ˆβ–ˆβ–Š | 9/32 [00:00<00:04, 5.48it/s]
31%|β–ˆβ–ˆβ–ˆβ– | 10/32 [00:00<00:04, 5.48it/s]
34%|β–ˆβ–ˆβ–ˆβ– | 11/32 [00:00<00:03, 5.48it/s]
38%|β–ˆβ–ˆβ–ˆβ–Š | 12/32 [00:00<00:03, 5.48it/s]
41%|β–ˆβ–ˆβ–ˆβ–ˆ | 13/32 [00:00<00:03, 5.48it/s]
44%|β–ˆβ–ˆβ–ˆβ–ˆβ– | 14/32 [00:00<00:03, 5.48it/s]
47%|β–ˆβ–ˆβ–ˆβ–ˆβ–‹ | 15/32 [00:00<00:03, 5.48it/s]
50%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆ | 16/32 [00:00<00:00, 67.55it/s]
50%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆ | 16/32 [00:00<00:00, 67.55it/s]
53%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Ž | 17/32 [00:00<00:00, 67.55it/s]
56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹ | 18/32 [00:00<00:00, 67.55it/s]
59%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 19/32 [00:00<00:00, 67.55it/s]
62%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Ž | 20/32 [00:00<00:00, 67.55it/s]
66%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ | 21/32 [00:00<00:00, 67.55it/s]
69%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 22/32 [00:00<00:00, 67.55it/s]
72%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ– | 23/32 [00:00<00:00, 67.55it/s]
75%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ | 24/32 [00:00<00:00, 67.55it/s]
78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š | 25/32 [00:00<00:00, 67.55it/s]
81%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ– | 26/32 [00:00<00:00, 67.55it/s]
84%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ– | 27/32 [00:00<00:00, 67.55it/s]
88%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š | 28/32 [00:00<00:00, 67.55it/s]
91%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ | 29/32 [00:00<00:00, 67.55it/s]
94%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–| 30/32 [00:00<00:00, 67.55it/s]
97%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹| 31/32 [00:00<00:00, 97.61it/s]
97%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹| 31/32 [00:00<00:00, 97.61it/s]
100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 32/32 [00:00<00:00, 97.61it/s]
100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 32/32 [00:00<00:00, 80.39it/s]
> Eval on experience 0 (Task 0) from test stream ended.
Loss_Exp/eval_phase/test_stream/Task000/Exp000 = 2.9953
Top1_Acc_Exp/eval_phase/test_stream/Task000/Exp000 = 0.0535
-- Starting eval on experience 1 (Task 1) from test stream --
0it [00:00, ?it/s]
3%|β–Ž | 1/32 [00:00<00:00, 89.13it/s]
6%|β–‹ | 2/32 [00:00<00:00, 108.93it/s]
9%|β–‰ | 3/32 [00:00<00:00, 118.84it/s]
12%|β–ˆβ–Ž | 4/32 [00:00<00:00, 124.46it/s]
16%|β–ˆβ–Œ | 5/32 [00:00<00:00, 128.25it/s]
19%|β–ˆβ–‰ | 6/32 [00:00<00:00, 130.85it/s]
22%|β–ˆβ–ˆβ– | 7/32 [00:00<00:00, 132.77it/s]
25%|β–ˆβ–ˆβ–Œ | 8/32 [00:00<00:00, 134.25it/s]
28%|β–ˆβ–ˆβ–Š | 9/32 [00:00<00:00, 135.46it/s]
31%|β–ˆβ–ˆβ–ˆβ– | 10/32 [00:00<00:00, 136.49it/s]
34%|β–ˆβ–ˆβ–ˆβ– | 11/32 [00:00<00:00, 137.32it/s]
38%|β–ˆβ–ˆβ–ˆβ–Š | 12/32 [00:00<00:00, 137.57it/s]
41%|β–ˆβ–ˆβ–ˆβ–ˆ | 13/32 [00:00<00:00, 138.15it/s]
44%|β–ˆβ–ˆβ–ˆβ–ˆβ– | 14/32 [00:00<00:00, 138.62it/s]
44%|β–ˆβ–ˆβ–ˆβ–ˆβ– | 14/32 [00:00<00:00, 138.62it/s]
47%|β–ˆβ–ˆβ–ˆβ–ˆβ–‹ | 15/32 [00:00<00:00, 138.62it/s]
50%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆ | 16/32 [00:00<00:00, 138.62it/s]
53%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Ž | 17/32 [00:00<00:00, 138.62it/s]
56%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹ | 18/32 [00:00<00:00, 138.62it/s]
59%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 19/32 [00:00<00:00, 138.62it/s]
62%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Ž | 20/32 [00:00<00:00, 138.62it/s]
66%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ | 21/32 [00:00<00:00, 138.62it/s]
69%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‰ | 22/32 [00:00<00:00, 138.62it/s]
72%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ– | 23/32 [00:00<00:00, 138.62it/s]
75%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ | 24/32 [00:00<00:00, 138.62it/s]
78%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š | 25/32 [00:00<00:00, 138.62it/s]
81%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ– | 26/32 [00:00<00:00, 138.62it/s]
84%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ– | 27/32 [00:00<00:00, 138.62it/s]
88%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Š | 28/32 [00:00<00:00, 138.62it/s]
91%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ | 29/32 [00:00<00:00, 142.87it/s]
91%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ | 29/32 [00:00<00:00, 142.87it/s]
94%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–| 30/32 [00:00<00:00, 142.87it/s]
97%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹| 31/32 [00:00<00:00, 142.87it/s]
100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 32/32 [00:00<00:00, 142.87it/s]
100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 32/32 [00:00<00:00, 145.06it/s]
> Eval on experience 1 (Task 1) from test stream ended.
Loss_Exp/eval_phase/test_stream/Task001/Exp001 = 2.9961
Top1_Acc_Exp/eval_phase/test_stream/Task001/Exp001 = 0.0440
-- Starting eval on experience 2 (Task 2) from test stream --
0it [00:00, ?it/s]
3%|β–Ž | 1/32 [00:00<00:00, 107.83it/s]
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