ft_16_15e6_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) 85518.20016980171
Emissions (Co2eq in kg) 0.0517483439964675
CPU power (W) 42.5
GPU power (W) [No GPU]
RAM power (W) 3.75
CPU energy (kWh) 1.0095872364968062
GPU energy (kWh) [No GPU]
RAM energy (kWh) 0.0890803925655782
Consumed energy (kWh) 1.0986676290623876
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) 0.1646225353268683
Emissions (Co2eq in kg) 0.033494628399839

Note

12 juillet 2024

My Config

Config Value
checkpoint damgomz/fp_bs32_lr1e4_x4
model_name ft_16_15e6_x4
sequence_length 400
num_epoch 6
learning_rate 1.5e-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 0.705959 0.700052
1 0.275730 0.200150 0.934243
2 0.153785 0.215815 0.920248
3 0.097911 0.262812 0.919220
4 0.053090 0.295929 0.901924
5 0.027806 0.374022 0.931046
6 0.018686 0.370689 0.928756