---
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)    | 37993.74807047844  |
| Emissions (Co2eq in kg)  | 0.0229906147552034 |
| CPU power (W)            | 42.5  |
| GPU power (W)            | [No GPU]  |
| RAM power (W)            | 3.75  |
| CPU energy (kWh)         | 0.4485365634348655  |
| GPU energy (kWh)         | [No GPU]  |
| RAM energy (kWh)         | 0.0395765287543337  |
| Consumed energy (kWh)    | 0.4881130921891984  |
| 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)         | 0.07313796503567101  |
| Emissions (Co2eq in kg)  | 0.014880884660937389 |

## Note

19 juin 2024

## My Config

| Config                   | Value           |
|--------------------------|-----------------|
| checkpoint               | albert-base-v2  |
| model_name               | BERTrand_base_x2 |
| 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                | 36660 |

## Training and Testing steps






 
Epoch | Train Loss | Test Loss | F-beta Score | TN | FP | FN | TP
---|---|---|---|---|---|---|---
| 0 | 0.000000 | 0.762512 | 0.001627 | 753.000000 | 9.000000 | 765.000000 | 1.000000 |
| 1 | 0.285383 | 0.236045 | 0.945052 | 638.000000 | 124.000000 | 23.000000 | 743.000000 |
| 2 | 0.171418 | 0.223179 | 0.937339 | 662.000000 | 100.000000 | 36.000000 | 730.000000 |
| 3 | 0.113694 | 0.209987 | 0.938465 | 671.000000 | 91.000000 | 37.000000 | 729.000000 |
| 4 | 0.064221 | 0.242213 | 0.933953 | 674.000000 | 88.000000 | 42.000000 | 724.000000 |
| 5 | 0.041251 | 0.297383 | 0.924348 | 669.000000 | 93.000000 | 50.000000 | 716.000000 |
| 6 | 0.029554 | 0.291359 | 0.926215 | 690.000000 | 72.000000 | 53.000000 | 713.000000 |