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) | 71832.20314526558 |
Emissions (Co2eq in kg) | 0.0434667651147476 |
CPU power (W) | 42.5 |
GPU power (W) | [No GPU] |
RAM power (W) | 3.75 |
CPU energy (kWh) | 0.848017205489013 |
GPU energy (kWh) | [No GPU] |
RAM energy (kWh) | 0.0748244563599428 |
Consumed energy (kWh) | 0.9228416618489558 |
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) | 0.13827699105463623 |
Emissions (Co2eq in kg) | 0.028134279565229015 |
Note
19 juin 2024
My Config
Config | Value |
---|---|
checkpoint | albert-base-v2 |
model_name | ft_32_15e6_base_x2 |
sequence_length | 400 |
num_epoch | 6 |
learning_rate | 1.5e-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 | 0.725213 | 0.323829 |
1 | 0.308142 | 0.225736 | 0.909666 |
2 | 0.182370 | 0.253100 | 0.916715 |
3 | 0.127769 | 0.271641 | 0.909688 |
4 | 0.074474 | 0.293281 | 0.907815 |
5 | 0.042815 | 0.323060 | 0.914852 |
6 | 0.030504 | 0.367846 | 0.917341 |