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) | 92837.01576209068 |
Emissions (Co2eq in kg) | 0.0561770889990077 |
CPU power (W) | 42.5 |
GPU power (W) | [No GPU] |
RAM power (W) | 3.75 |
CPU energy (kWh) | 1.0959899695222557 |
GPU energy (kWh) | [No GPU] |
RAM energy (kWh) | 0.096704219539712 |
Consumed energy (kWh) | 1.192694189061968 |
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) | 0.17871125534202453 |
Emissions (Co2eq in kg) | 0.036361164506818845 |
Note
19 juin 2024
My Config
Config | Value |
---|---|
checkpoint | damgomz/fp_bs16_lr5_x4 |
model_name | ft_4_14e6_x4 |
sequence_length | 400 |
num_epoch | 6 |
learning_rate | 1.4e-05 |
batch_size | 4 |
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 | 0.702670 | 0.510963 |
1 | 0.266945 | 0.208224 | 0.924556 |
2 | 0.165049 | 0.222903 | 0.941403 |
3 | 0.101503 | 0.283321 | 0.923648 |
4 | 0.056364 | 0.321558 | 0.920182 |
5 | 0.039267 | 0.372677 | 0.916073 |
6 | 0.029807 | 0.334020 | 0.924210 |