---
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)    | 72691.67709064484  |
| Emissions (Co2eq in kg)  | 0.0439868478257266 |
| CPU power (W)            | 42.5  |
| GPU power (W)            | [No GPU]  |
| RAM power (W)            | 3.75  |
| CPU energy (kWh)         | 0.8581637735386716  |
| GPU energy (kWh)         | [No GPU]  |
| RAM energy (kWh)         | 0.0757197496503593  |
| Consumed energy (kWh)    | 0.9338835231890332  |
| 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)         | 0.1399314783994913  |
| Emissions (Co2eq in kg)  | 0.02847090686050256 |

## Note

19 juin 2024

## My Config

| Config                   | Value           |
|--------------------------|-----------------|
| checkpoint               | albert-base-v2  |
| model_name               | ft_32_4e6_base_x8 |
| sequence_length          | 400  |
| num_epoch                | 6  |
| learning_rate            | 4e-06  |
| 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 | 0.764698 | 0.508976 |
| 1 | 0.378353 | 0.279458 | 0.901742 |
| 2 | 0.240503 | 0.258632 | 0.891390 |
| 3 | 0.198528 | 0.230921 | 0.910689 |
| 4 | 0.172870 | 0.249744 | 0.908769 |
| 5 | 0.146713 | 0.229990 | 0.928140 |
| 6 | 0.123440 | 0.235008 | 0.912746 |