ft_4_16e6_x4 / README.md
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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) 96027.81192708015
Emissions (Co2eq in kg) 0.0581078865146315
CPU power (W) 42.5
GPU power (W) [No GPU]
RAM power (W) 3.75
CPU energy (kWh) 1.1336590559254125
GPU energy (kWh) [No GPU]
RAM energy (kWh) 0.1000278406294686
Consumed energy (kWh) 1.2336868965548835
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) 0.1848535379596293
Emissions (Co2eq in kg) 0.03761089300477306

Note

12 juillet 2024

My Config

Config Value
checkpoint damgomz/fp_bs32_lr1e4_x4
model_name ft_4_16e6_x4
sequence_length 400
num_epoch 6
learning_rate 1.6e-05
batch_size 4
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 0.712591 0.487024
1 0.256756 0.235128 0.949143
2 0.156550 0.212925 0.928885
3 0.091505 0.253246 0.918680
4 0.050380 0.294809 0.922108
5 0.028062 0.415338 0.923676
6 0.023918 0.345038 0.924848