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) | 76463.57305526733 |
Emissions (Co2eq in kg) | 0.0462692720003635 |
CPU power (W) | 42.5 |
GPU power (W) | [No GPU] |
RAM power (W) | 3.75 |
CPU energy (kWh) | 0.9026928755258524 |
GPU energy (kWh) | [No GPU] |
RAM energy (kWh) | 0.0796487308171892 |
Consumed energy (kWh) | 0.9823416063430404 |
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) | 0.1471923781313896 |
Emissions (Co2eq in kg) | 0.029948232779979704 |
Note
19 juin 2024
My Config
Config | Value |
---|---|
checkpoint | albert-base-v2 |
model_name | ft_32_16e6_base_x2 |
sequence_length | 400 |
num_epoch | 6 |
learning_rate | 1.6e-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 | 0.737350 | 0.165081 |
1 | 0.311884 | 0.222528 | 0.926436 |
2 | 0.176962 | 0.214609 | 0.916218 |
3 | 0.122318 | 0.246520 | 0.919283 |
4 | 0.072663 | 0.304516 | 0.886896 |
5 | 0.044193 | 0.331732 | 0.917947 |
6 | 0.030915 | 0.362305 | 0.895415 |