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README.md
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---
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language: en
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tags:
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cpu_power: 42.5
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gpu_power: 0.0
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ram_power: 3.75
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cpu_energy: 0.9166553569457598
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gpu_energy: 0
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ram_energy: 0.0808807764212289
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energy_consumed: 0.9975361333669904
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country_name: Switzerland
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country_iso_code: CHE
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region: .nan
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cloud_provider: .nan
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cloud_region: .nan
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os: Linux-5.14.0-70.30.1.el9_0.x86_64-x86_64-with-glibc2.34
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python_version: 3.10.4
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codecarbon_version: 2.3.4
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cpu_count: 2
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cpu_model: Intel(R) Xeon(R) Platinum 8360Y CPU @ 2.40GHz
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gpu_count: .nan
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gpu_model: .nan
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longitude: .nan
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latitude: .nan
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ram_total_size: 10
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tracking_mode: machine
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on_cloud: N
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pue: 1.0
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---
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## Environmental Impact (CODE CARBON DEFAULT)
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| Metric | Value |
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|--------------------------|---------------------------------|
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| Duration (in seconds) |
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| Emissions (Co2eq in kg) |
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| CPU power (W) |
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| GPU power (W) | [No GPU] |
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| RAM power (W) |
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| CPU energy (kWh) |
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| GPU energy (kWh) | [No GPU] |
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| RAM energy (kWh) |
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| Consumed energy (kWh) |
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| Country name |
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| Cloud provider |
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| Cloud region |
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| CPU count |
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| CPU model |
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| GPU count |
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| GPU model |
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## Environmental Impact (for one core)
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| Metric | Value |
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|--------------------------|---------------------------------|
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| CPU energy (kWh) |
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| Emissions (Co2eq in kg) |
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## Note
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## My Config
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| drop_out_prob | 0.1 |
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| packing_length | 100 |
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| train_test_split | 0.2 |
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| num_steps |
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## Training and Testing steps
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Epoch | Train Loss | Test Loss | F-beta Score
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---|---|---|---
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| 0 | 0.000000 | 0.
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| 1 | 0.
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| 2 | 0.350543 | 0.359614 | 0.848509 |
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| 3 | 0.307174 | 0.356749 | 0.863032 |
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| 4 | 0.262458 | 0.385538 | 0.850415 |
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| 5 | 0.210636 | 0.417394 | 0.822958 |
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| 6 | 0.150231 | 0.471214 | 0.824738 |
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---
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language: en
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tags:
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- text-classification
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pipeline_tag: text-classification
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widget:
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- text: GEPS Techno is the pioneer of hybridization of renewable energies at sea.
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We imagine, design and commercialize innovative off-grid systems that aim to generate
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power at sea, stabilize and collect data. The success of our low power platforms
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WAVEPEAL enabled us to scale-up the device up to WAVEGEM, the 150-kW capacity
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platform.
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---
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## Environmental Impact (CODE CARBON DEFAULT)
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| Metric | Value |
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|--------------------------|---------------------------------|
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| Duration (in seconds) | [More Information Needed] |
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| Emissions (Co2eq in kg) | [More Information Needed] |
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| CPU power (W) | [NO CPU] |
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| GPU power (W) | [No GPU] |
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| RAM power (W) | [More Information Needed] |
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| CPU energy (kWh) | [No CPU] |
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| GPU energy (kWh) | [No GPU] |
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| RAM energy (kWh) | [More Information Needed] |
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| Consumed energy (kWh) | [More Information Needed] |
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| Country name | [More Information Needed] |
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| Cloud provider | [No Cloud] |
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| Cloud region | [No Cloud] |
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| CPU count | [No CPU] |
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| CPU model | [No CPU] |
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| GPU count | [No GPU] |
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| GPU model | [No GPU] |
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## Environmental Impact (for one core)
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| Metric | Value |
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|--------------------------|---------------------------------|
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| CPU energy (kWh) | [No CPU] |
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| Emissions (Co2eq in kg) | [More Information Needed] |
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## Note
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+
14 juin 2024
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## My Config
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| drop_out_prob | 0.1 |
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| packing_length | 100 |
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| train_test_split | 0.2 |
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| num_steps | 29328 |
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## Training and Testing steps
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Epoch | Train Loss | Test Loss | F-beta Score
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---|---|---|---
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| 0 | 0.000000 | 0.678359 | 0.710652 |
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| 1 | 0.330838 | 0.256687 | 0.887480 |
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