ft_4_17e6_x2 / 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) 94193.79744768144
Emissions (Co2eq in kg) 0.0569980947595841
CPU power (W) 42.5
GPU power (W) [No GPU]
RAM power (W) 3.75
CPU energy (kWh) 1.112007470722169
GPU energy (kWh) [No GPU]
RAM energy (kWh) 0.0981174684422712
Consumed energy (kWh) 1.2101249391644375
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) 0.18132306008678678
Emissions (Co2eq in kg) 0.036892570667008566

Note

12 juillet 2024

My Config

Config Value
checkpoint damgomz/fp_bs16_lr1e4_x2
model_name ft_4_17e6_x2
sequence_length 400
num_epoch 6
learning_rate 1.7e-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 0.716950 0.494992
1 0.294474 0.210283 0.936422
2 0.169180 0.209291 0.923463
3 0.109349 0.239753 0.928542
4 0.067060 0.297160 0.910511
5 0.049154 0.309301 0.903968
6 0.053286 0.337630 0.920875