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) | 84062.48010516167 |
Emissions (Co2eq in kg) | 0.0508674646679311 |
CPU power (W) | 42.5 |
GPU power (W) | [No GPU] |
RAM power (W) | 3.75 |
CPU energy (kWh) | 0.992401616716054 |
GPU energy (kWh) | [No GPU] |
RAM energy (kWh) | 0.0875640882144371 |
Consumed energy (kWh) | 1.0799657049304925 |
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) | 0.1618202742024362 |
Emissions (Co2eq in kg) | 0.032924471374521654 |
Note
12 juillet 2024
My Config
Config | Value |
---|---|
checkpoint | damgomz/fp_bs32_lr1e4_x8 |
model_name | ft_16_14e6_x8 |
sequence_length | 400 |
num_epoch | 6 |
learning_rate | 1.4e-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 | 0.715655 | 0.166667 |
1 | 0.279694 | 0.226171 | 0.910593 |
2 | 0.165815 | 0.216642 | 0.931521 |
3 | 0.107897 | 0.243272 | 0.914448 |
4 | 0.062500 | 0.286829 | 0.910832 |
5 | 0.041202 | 0.310174 | 0.926196 |
6 | 0.024451 | 0.363134 | 0.903604 |