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) | [More Information Needed] |
| Emissions (Co2eq in kg) | [More Information Needed] |
| CPU power (W) | [NO CPU] |
| GPU power (W) | [No GPU] |
| RAM power (W) | [More Information Needed] |
| CPU energy (kWh) | [No CPU] |
| GPU energy (kWh) | [No GPU] |
| RAM energy (kWh) | [More Information Needed] |
| Consumed energy (kWh) | [More Information Needed] |
| Country name | [More Information Needed] |
| Cloud provider | [No Cloud] |
| Cloud region | [No Cloud] |
| CPU count | [No CPU] |
| CPU model | [No CPU] |
| GPU count | [No GPU] |
| GPU model | [No GPU] |
Environmental Impact (for one core)
| Metric | Value |
|---|---|
| CPU energy (kWh) | [No CPU] |
| Emissions (Co2eq in kg) | [More Information Needed] |
Note
19 juin 2024
My Config
| Config | Value |
|---|---|
| checkpoint | damgomz/fp_bs32_lr1e4_x8 |
| model_name | B_x8 |
| sequence_length | 400 |
| num_epoch | 2 |
| learning_rate | 1.8e-05 |
| batch_size | 8 |
| weight_decay | 0.0 |
| warm_up_prop | 0.0 |
| drop_out_prob | 0.1 |
| packing_length | 100 |
| train_test_split | 0.2 |
| num_steps | 12220 |
Training and Testing steps
| Epoch | Train Loss | Test Loss | F-beta Score | TN | FP | FN | TP |
|---|---|---|---|---|---|---|---|
| 0 | 0.000000 | 0.695801 | 0.000000 | 761.000000 | 1.000000 | 766.000000 | 0.000000 |
| 1 | 0.247787 | 0.225137 | 0.917837 | 686.000000 | 76.000000 | 60.000000 | 706.000000 |
| 2 | 0.160151 | 0.223627 | 0.929874 | 657.000000 | 105.000000 | 42.000000 | 724.000000 |