metadata
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) | 2598.8059442043304 |
| Emissions (Co2eq in kg) | 0.0015725783810144 |
| CPU power (W) | 42.5 |
| GPU power (W) | [No GPU] |
| RAM power (W) | 3.75 |
| CPU energy (kWh) | 0.0306802982341912 |
| GPU energy (kWh) | [No GPU] |
| RAM energy (kWh) | 0.0027070689345399 |
| Consumed energy (kWh) | 0.0333873671687311 |
| 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) | 0.005002701442593336 |
| Emissions (Co2eq in kg) | 0.0010178656614800293 |
Note
19 juin 2024
My Config
| Config | Value |
|---|---|
| checkpoint | damgomz/fp_bs32_lr1e4_x1 |
| model_name | B_x1 |
| sequence_length | 400 |
| num_epoch | 1 |
| learning_rate | 1.9e-05 |
| batch_size | 4 |
| weight_decay | 0.0 |
| warm_up_prop | 0.0 |
| drop_out_prob | 0.1 |
| packing_length | 100 |
| train_test_split | 0.2 |
| num_steps | 6110 |
Training and Testing steps
| Epoch | Train Loss | Test Loss | F-beta Score | TN | FP | FN | TP |
|---|---|---|---|---|---|---|---|
| 0 | 0.000000 | 0.705966 | 0.827322 | 8.000000 | 754.000000 | 9.000000 | 757.000000 |
| 1 | 0.239991 | 0.199943 | 0.919166 | 696.000000 | 66.000000 | 61.000000 | 705.000000 |