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) | 78158.4726319313 |
Emissions (Co2eq in kg) | 0.0472948750017108 |
CPU power (W) | 42.5 |
GPU power (W) | [No GPU] |
RAM power (W) | 3.75 |
CPU energy (kWh) | 0.9227019708373492 |
GPU energy (kWh) | [No GPU] |
RAM energy (kWh) | 0.0814141838453706 |
Consumed energy (kWh) | 1.0041161546827222 |
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) | 0.15045505981646778 |
Emissions (Co2eq in kg) | 0.030612068447506427 |
Note
19 juin 2024
My Config
Config | Value |
---|---|
checkpoint | albert-base-v2 |
model_name | ft_16_16e6_base_x1 |
sequence_length | 400 |
num_epoch | 6 |
learning_rate | 1.6e-05 |
batch_size | 16 |
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 | 0.722742 | 0.277531 |
1 | 0.307390 | 0.238249 | 0.902306 |
2 | 0.191545 | 0.221179 | 0.910911 |
3 | 0.143701 | 0.235340 | 0.918727 |
4 | 0.101185 | 0.256751 | 0.919708 |
5 | 0.068797 | 0.272793 | 0.932906 |
6 | 0.053657 | 0.312024 | 0.919134 |