| | --- |
| | language: en |
| | tags: |
| | - text-classification |
| | pipeline_tag: text-classification |
| | widget: |
| | - text: GEPS Techno is the pioneer of hybridization of renewable energies at sea. |
| | We imagine, design and commercialize innovative off-grid systems that aim to generate |
| | power at sea, stabilize and collect data. The success of our low power platforms |
| | WAVEPEAL enabled us to scale-up the device up to WAVEGEM, the 150-kW capacity |
| | platform. |
| | --- |
| | |
| | ## Environmental Impact (CODE CARBON DEFAULT) |
| |
|
| | | Metric | Value | |
| | |--------------------------|---------------------------------| |
| | | Duration (in seconds) | 37993.74807047844 | |
| | | Emissions (Co2eq in kg) | 0.0229906147552034 | |
| | | CPU power (W) | 42.5 | |
| | | GPU power (W) | [No GPU] | |
| | | RAM power (W) | 3.75 | |
| | | CPU energy (kWh) | 0.4485365634348655 | |
| | | GPU energy (kWh) | [No GPU] | |
| | | RAM energy (kWh) | 0.0395765287543337 | |
| | | Consumed energy (kWh) | 0.4881130921891984 | |
| | | Country name | Switzerland | |
| | | Cloud provider | nan | |
| | | Cloud region | nan | |
| | | CPU count | 2 | |
| | | CPU model | Intel(R) Xeon(R) Platinum 8360Y CPU @ 2.40GHz | |
| | | GPU count | nan | |
| | | GPU model | nan | |
| |
|
| | ## Environmental Impact (for one core) |
| |
|
| | | Metric | Value | |
| | |--------------------------|---------------------------------| |
| | | CPU energy (kWh) | 0.07313796503567101 | |
| | | Emissions (Co2eq in kg) | 0.014880884660937389 | |
| |
|
| | ## Note |
| |
|
| | 19 juin 2024 |
| |
|
| | ## My Config |
| |
|
| | | Config | Value | |
| | |--------------------------|-----------------| |
| | | checkpoint | albert-base-v2 | |
| | | model_name | BERTrand_base_x2 | |
| | | sequence_length | 400 | |
| | | num_epoch | 6 | |
| | | learning_rate | 9e-06 | |
| | | batch_size | 16 | |
| | | weight_decay | 0.0 | |
| | | warm_up_prop | 0.0 | |
| | | drop_out_prob | 0.1 | |
| | | packing_length | 100 | |
| | | train_test_split | 0.2 | |
| | | num_steps | 36660 | |
| |
|
| | ## Training and Testing steps |
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| | Epoch | Train Loss | Test Loss | F-beta Score | TN | FP | FN | TP |
| | ---|---|---|---|---|---|---|--- |
| | | 0 | 0.000000 | 0.762512 | 0.001627 | 753.000000 | 9.000000 | 765.000000 | 1.000000 | |
| | | 1 | 0.285383 | 0.236045 | 0.945052 | 638.000000 | 124.000000 | 23.000000 | 743.000000 | |
| | | 2 | 0.171418 | 0.223179 | 0.937339 | 662.000000 | 100.000000 | 36.000000 | 730.000000 | |
| | | 3 | 0.113694 | 0.209987 | 0.938465 | 671.000000 | 91.000000 | 37.000000 | 729.000000 | |
| | | 4 | 0.064221 | 0.242213 | 0.933953 | 674.000000 | 88.000000 | 42.000000 | 724.000000 | |
| | | 5 | 0.041251 | 0.297383 | 0.924348 | 669.000000 | 93.000000 | 50.000000 | 716.000000 | |
| | | 6 | 0.029554 | 0.291359 | 0.926215 | 690.000000 | 72.000000 | 53.000000 | 713.000000 | |
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