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) | 59384.87842345238 |
| Emissions (Co2eq in kg) | 0.035934717874685 |
| CPU power (W) | 42.5 |
| GPU power (W) | [No GPU] |
| RAM power (W) | 3.75 |
| CPU energy (kWh) | 0.7010702273961583 |
| GPU energy (kWh) | [No GPU] |
| RAM energy (kWh) | 0.0618587523428103 |
| Consumed energy (kWh) | 0.7629289797389662 |
| 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) | 0.11431589096514581 |
| Emissions (Co2eq in kg) | 0.023259077382518846 |
Note
19 juin 2024
My Config
| Config | Value |
|---|---|
| checkpoint | albert-base-v2 |
| model_name | ft_16_9e6_base_x8 |
| sequence_length | 400 |
| num_epoch | 6 |
| learning_rate | 9e-06 |
| 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 | 0.722126 | 0.633520 |
| 1 | 0.321459 | 0.235528 | 0.913582 |
| 2 | 0.202470 | 0.226941 | 0.903546 |
| 3 | 0.163656 | 0.222033 | 0.927337 |
| 4 | 0.122813 | 0.246447 | 0.919569 |
| 5 | 0.082514 | 0.294264 | 0.922449 |
| 6 | 0.056816 | 0.326609 | 0.916088 |