---
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)    | 83441.01578950882  |
| Emissions (Co2eq in kg)  | 0.0504914069538166 |
| CPU power (W)            | 42.5  |
| GPU power (W)            | [No GPU]  |
| RAM power (W)            | 3.75  |
| CPU energy (kWh)         | 0.98506498173227  |
| GPU energy (kWh)         | [No GPU]  |
| RAM energy (kWh)         | 0.0869166524966554  |
| Consumed energy (kWh)    | 1.0719816342289268  |
| 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)         | 0.16062395539480448  |
| Emissions (Co2eq in kg)  | 0.032681064517557624 |

## Note

19 juin 2024

## My Config

| Config                   | Value           |
|--------------------------|-----------------|
| checkpoint               | albert-base-v2  |
| model_name               | ft_16_9e6_base_x1 |
| 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 | 0.727082 | 0.304616 |
| 1 | 0.316126 | 0.230286 | 0.906445 |
| 2 | 0.190042 | 0.221763 | 0.905844 |
| 3 | 0.141104 | 0.224095 | 0.929108 |
| 4 | 0.091876 | 0.253269 | 0.910210 |
| 5 | 0.056768 | 0.281068 | 0.932853 |
| 6 | 0.044041 | 0.297247 | 0.916953 |