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) | 78313.53327870369 |
Emissions (Co2eq in kg) | 0.0473887137294402 |
CPU power (W) | 42.5 |
GPU power (W) | [No GPU] |
RAM power (W) | 3.75 |
CPU energy (kWh) | 0.9245326654970666 |
GPU energy (kWh) | [No GPU] |
RAM energy (kWh) | 0.0815757765623429 |
Consumed energy (kWh) | 1.0061084420594089 |
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) | 0.1507535515615046 |
Emissions (Co2eq in kg) | 0.030672800534158943 |
Note
19 juin 2024
My Config
Config | Value |
---|---|
checkpoint | albert-base-v2 |
model_name | ft_32_16e6_base_x8 |
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 | 29328 |
Training and Testing steps
Epoch | Train Loss | Test Loss | F-beta Score |
---|---|---|---|
0 | 0.000000 | 0.733605 | 0.521574 |
1 | 0.343848 | 0.250949 | 0.927429 |
2 | 0.207227 | 0.216056 | 0.905269 |
3 | 0.158365 | 0.231901 | 0.928852 |
4 | 0.115495 | 0.261195 | 0.920515 |
5 | 0.076285 | 0.315937 | 0.903032 |
6 | 0.055799 | 0.309163 | 0.927541 |