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) | 64439.61116409302 |
Emissions (Co2eq in kg) | 0.038993406428673 |
CPU power (W) | 42.5 |
GPU power (W) | [No GPU] |
RAM power (W) | 3.75 |
CPU energy (kWh) | 0.7607439085890851 |
GPU energy (kWh) | [No GPU] |
RAM energy (kWh) | 0.067124001405885 |
Consumed energy (kWh) | 0.8278679099949702 |
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) | 0.12404625149087906 |
Emissions (Co2eq in kg) | 0.025238847705936433 |
Note
19 juin 2024
My Config
Config | Value |
---|---|
checkpoint | albert-base-v2 |
model_name | ft_32_10e6_base_x8 |
sequence_length | 400 |
num_epoch | 6 |
learning_rate | 1e-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 | 0.722382 | 0.623123 |
1 | 0.342272 | 0.250376 | 0.902948 |
2 | 0.212349 | 0.227735 | 0.926831 |
3 | 0.174827 | 0.249475 | 0.931909 |
4 | 0.133557 | 0.247448 | 0.923699 |
5 | 0.092758 | 0.272226 | 0.916025 |
6 | 0.067174 | 0.297975 | 0.923680 |