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) | 82536.04255104065 |
Emissions (Co2eq in kg) | 0.0499437995576998 |
CPU power (W) | 42.5 |
GPU power (W) | [No GPU] |
RAM power (W) | 3.75 |
CPU energy (kWh) | 0.9743813026997792 |
GPU energy (kWh) | [No GPU] |
RAM energy (kWh) | 0.085974094376713 |
Consumed energy (kWh) | 1.060355397076493 |
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) | 0.15888188191075323 |
Emissions (Co2eq in kg) | 0.03232661666582425 |
Note
19 juin 2024
My Config
Config | Value |
---|---|
checkpoint | albert-base-v2 |
model_name | ft_32_19e6_base_x4 |
sequence_length | 400 |
num_epoch | 6 |
learning_rate | 1.9e-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 | 0.716812 | 0.321399 |
1 | 0.316622 | 0.222771 | 0.923284 |
2 | 0.188987 | 0.254623 | 0.899390 |
3 | 0.140403 | 0.233587 | 0.925130 |
4 | 0.091719 | 0.278762 | 0.922702 |
5 | 0.055096 | 0.395175 | 0.882975 |
6 | 0.044405 | 0.355451 | 0.910667 |