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) | 62964.56637644768 |
| Emissions (Co2eq in kg) | 0.038100857459098 |
| CPU power (W) | 42.5 |
| GPU power (W) | [No GPU] |
| RAM power (W) | 3.75 |
| CPU energy (kWh) | 0.7433305791758832 |
| GPU energy (kWh) | [No GPU] |
| RAM energy (kWh) | 0.065587648868064 |
| Consumed energy (kWh) | 0.8089182280439484 |
| 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) | 0.12120679027466177 |
| Emissions (Co2eq in kg) | 0.02466112183077534 |
Note
19 juin 2024
My Config
| Config | Value |
|---|---|
| checkpoint | damgomz/fp_bs8_lr1e4_x12 |
| model_name | BERTrand_x12 |
| sequence_length | 400 |
| num_epoch | 6 |
| learning_rate | 9e-06 |
| batch_size | 1 |
| 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
| Epoch | Train Loss | Test Loss | F-beta Score | TN | FP | FN | TP |
|---|---|---|---|---|---|---|---|
| 0 | 0.000000 | 0.706886 | 0.832244 | 0.000000 | 762.000000 | 2.000000 | 764.000000 |
| 1 | 0.255234 | 0.215122 | 0.937741 | 668.000000 | 94.000000 | 37.000000 | 729.000000 |
| 2 | 0.133187 | 0.232388 | 0.926596 | 674.000000 | 88.000000 | 49.000000 | 717.000000 |
| 3 | 0.042523 | 0.346472 | 0.934866 | 643.000000 | 119.000000 | 34.000000 | 732.000000 |
| 4 | 0.008232 | 0.495148 | 0.917598 | 685.000000 | 77.000000 | 60.000000 | 706.000000 |
| 5 | 0.003022 | 0.573862 | 0.928167 | 663.000000 | 99.000000 | 45.000000 | 721.000000 |
| 6 | 0.000739 | 0.586513 | 0.918765 | 681.000000 | 81.000000 | 58.000000 | 708.000000 |