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) | 145185.28997969627 |
Emissions (Co2eq in kg) | 0.0878538339675317 |
CPU power (W) | 42.5 |
GPU power (W) | [No GPU] |
RAM power (W) | 3.75 |
CPU energy (kWh) | 1.7139891845208104 |
GPU energy (kWh) | [No GPU] |
RAM energy (kWh) | 0.1512330818330255 |
Consumed energy (kWh) | 1.8652222663538292 |
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) | 0.2794816832109153 |
Emissions (Co2eq in kg) | 0.05686423857538103 |
Note
12 juillet 2024
My Config
Config | Value |
---|---|
checkpoint | damgomz/fp_bs32_lr1e4_x8 |
model_name | ft_1_1e6_x8 |
sequence_length | 400 |
num_epoch | 6 |
learning_rate | 1e-06 |
batch_size | 1 |
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 | 0.704741 | 0.499602 |
1 | 0.311299 | 0.223562 | 0.913359 |
2 | 0.190257 | 0.210860 | 0.935717 |
3 | 0.153828 | 0.210610 | 0.930389 |
4 | 0.121913 | 0.230693 | 0.911285 |
5 | 0.096213 | 0.243568 | 0.922208 |
6 | 0.079274 | 0.250193 | 0.917204 |