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) | 106946.20297837256 |
Emissions (Co2eq in kg) | 0.0647147449117574 |
CPU power (W) | 42.5 |
GPU power (W) | [No GPU] |
RAM power (W) | 3.75 |
CPU energy (kWh) | 1.2625559734529868 |
GPU energy (kWh) | [No GPU] |
RAM energy (kWh) | 0.1114009470318752 |
Consumed energy (kWh) | 1.3739569204848612 |
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) | 0.20587144073336716 |
Emissions (Co2eq in kg) | 0.04188726283319592 |
Note
14 juin 2024
My Config
Config | Value |
---|---|
checkpoint | albert-base-v2 |
model_name | ft_2_8e6_base_x1 |
sequence_length | 400 |
num_epoch | 6 |
learning_rate | 8e-06 |
batch_size | 2 |
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 | 0.704057 | 0.560617 |
1 | 0.295263 | 0.235874 | 0.927627 |
2 | 0.197611 | 0.217753 | 0.908701 |
3 | 0.148565 | 0.219733 | 0.928400 |
4 | 0.103731 | 0.265954 | 0.925723 |
5 | 0.066320 | 0.283512 | 0.928518 |
6 | 0.037954 | 0.345470 | 0.904341 |