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) | 148133.22635698318 |
Emissions (Co2eq in kg) | 0.0896376804453751 |
CPU power (W) | 42.5 |
GPU power (W) | [No GPU] |
RAM power (W) | 3.75 |
CPU energy (kWh) | 1.7487911976191746 |
GPU energy (kWh) | [No GPU] |
RAM energy (kWh) | 0.1543038628970579 |
Consumed energy (kWh) | 1.9030950605162344 |
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) | 0.28515646073719264 |
Emissions (Co2eq in kg) | 0.058018846989818414 |
Note
14 juin 2024
My Config
Config | Value |
---|---|
checkpoint | damgomz/fp_bs16_lr5_x12 |
model_name | ft_1_4e6_x12 |
sequence_length | 400 |
num_epoch | 6 |
learning_rate | 4e-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 | 0.699794 | 0.045148 |
1 | 0.262525 | 0.216921 | 0.933297 |
2 | 0.166312 | 0.210638 | 0.921581 |
3 | 0.104171 | 0.247054 | 0.916739 |
4 | 0.053817 | 0.301459 | 0.917378 |
5 | 0.025530 | 0.350777 | 0.915204 |
6 | 0.012781 | 0.379057 | 0.912054 |