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) | 54853.55023550987 |
| Emissions (Co2eq in kg) | 0.0331927480539131 |
| CPU power (W) | 42.5 |
| GPU power (W) | [No GPU] |
| RAM power (W) | 3.75 |
| CPU energy (kWh) | 0.6475755910164785 |
| GPU energy (kWh) | [No GPU] |
| RAM energy (kWh) | 0.0571387049414216 |
| Consumed energy (kWh) | 0.7047142959579017 |
| 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) | 0.1055930842033565 |
| Emissions (Co2eq in kg) | 0.021484307175574698 |
Note
19 juin 2024
My Config
| Config | Value |
|---|---|
| checkpoint | albert-base-v2 |
| model_name | ft_16_12e6_base_x12 |
| sequence_length | 400 |
| num_epoch | 6 |
| learning_rate | 1.2e-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 | 0.703030 | 0.501482 |
| 1 | 0.353583 | 0.258170 | 0.916336 |
| 2 | 0.223726 | 0.254544 | 0.894809 |
| 3 | 0.185908 | 0.220265 | 0.928670 |
| 4 | 0.145264 | 0.254963 | 0.930168 |
| 5 | 0.116385 | 0.237453 | 0.926435 |
| 6 | 0.088435 | 0.291192 | 0.930136 |