| | --- |
| | 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) | 47077.0361263752 | |
| | | Emissions (Co2eq in kg) | 0.0284870557510473 | |
| | | CPU power (W) | 42.5 | |
| | | GPU power (W) | [No GPU] | |
| | | RAM power (W) | 3.75 | |
| | | CPU energy (kWh) | 0.5557696538744712 | |
| | | GPU energy (kWh) | [No GPU] | |
| | | RAM energy (kWh) | 0.0490382217767338 | |
| | | Consumed energy (kWh) | 0.6048078756512043 | |
| | | 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) | 0.09062329454327225 | |
| | | Emissions (Co2eq in kg) | 0.01843850581616362 | |
| |
|
| | ## Note |
| |
|
| | 19 juin 2024 |
| |
|
| | ## My Config |
| |
|
| | | Config | Value | |
| | |--------------------------|-----------------| |
| | | checkpoint | damgomz/fp_bs16_lr1e4_x2 | |
| | | model_name | BERTrand_x2 | |
| | | sequence_length | 400 | |
| | | num_epoch | 6 | |
| | | learning_rate | 5e-06 | |
| | | batch_size | 2 | |
| | | 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 | 0.697500 | 0.004883 | 757.000000 | 5.000000 | 763.000000 | 3.000000 | |
| | | 1 | 0.277993 | 0.215116 | 0.936614 | 672.000000 | 90.000000 | 39.000000 | 727.000000 | |
| | | 2 | 0.172936 | 0.216522 | 0.935484 | 676.000000 | 86.000000 | 41.000000 | 725.000000 | |
| | | 3 | 0.124307 | 0.222397 | 0.927996 | 693.000000 | 69.000000 | 52.000000 | 714.000000 | |
| | | 4 | 0.062651 | 0.255473 | 0.935808 | 673.000000 | 89.000000 | 40.000000 | 726.000000 | |
| | | 5 | 0.026753 | 0.345185 | 0.920094 | 691.000000 | 71.000000 | 59.000000 | 707.000000 | |
| | | 6 | 0.015767 | 0.408288 | 0.921737 | 689.000000 | 73.000000 | 57.000000 | 709.000000 | |
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