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) | 58472.9090526104 |
Emissions (Co2eq in kg) | 0.0353828713730564 |
CPU power (W) | 42.5 |
GPU power (W) | [No GPU] |
RAM power (W) | 3.75 |
CPU energy (kWh) | 0.6903039364420729 |
GPU energy (kWh) | [No GPU] |
RAM energy (kWh) | 0.0609088058151305 |
Consumed energy (kWh) | 0.7512127422572015 |
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) | 0.112560349926275 |
Emissions (Co2eq in kg) | 0.02290188937893907 |
Note
19 juin 2024
My Config
Config | Value |
---|---|
checkpoint | albert-base-v2 |
model_name | ft_32_13e6_base_x4 |
sequence_length | 400 |
num_epoch | 6 |
learning_rate | 1.3e-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 | 0.769925 | 0.338207 |
1 | 0.318355 | 0.234563 | 0.926135 |
2 | 0.195246 | 0.224179 | 0.909345 |
3 | 0.144236 | 0.233321 | 0.929572 |
4 | 0.095344 | 0.285724 | 0.918945 |
5 | 0.062180 | 0.348233 | 0.910088 |
6 | 0.041635 | 0.362033 | 0.907800 |