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) | 38957.92519903183 |
| Emissions (Co2eq in kg) | 0.0235740501238812 |
| CPU power (W) | 42.5 |
| GPU power (W) | [No GPU] |
| RAM power (W) | 3.75 |
| CPU energy (kWh) | 0.4599191364260191 |
| GPU energy (kWh) | [No GPU] |
| RAM energy (kWh) | 0.040580855588615 |
| Consumed energy (kWh) | 0.5004999920146328 |
| 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) | 0.07499400600813627 |
| Emissions (Co2eq in kg) | 0.015258520702954134 |
Note
19 juin 2024
My Config
| Config | Value |
|---|---|
| checkpoint | albert-base-v2 |
| model_name | BERTrand_base_x4 |
| sequence_length | 400 |
| num_epoch | 6 |
| learning_rate | 1.6e-05 |
| batch_size | 32 |
| 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 | 0.729831 | 0.607085 | 56.000000 | 706.000000 | 245.000000 | 521.000000 |
| 1 | 0.289319 | 0.223377 | 0.917121 | 683.000000 | 79.000000 | 60.000000 | 706.000000 |
| 2 | 0.192557 | 0.244767 | 0.953641 | 614.000000 | 148.000000 | 9.000000 | 757.000000 |
| 3 | 0.141159 | 0.227885 | 0.913123 | 693.000000 | 69.000000 | 66.000000 | 700.000000 |
| 4 | 0.098399 | 0.224589 | 0.938067 | 691.000000 | 71.000000 | 42.000000 | 724.000000 |
| 5 | 0.051018 | 0.279528 | 0.915383 | 698.000000 | 64.000000 | 65.000000 | 701.000000 |
| 6 | 0.040902 | 0.293502 | 0.934194 | 675.000000 | 87.000000 | 42.000000 | 724.000000 |