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language: en |
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tags: |
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- fill-mask |
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## Environmental Impact (CODE CARBON DEFAULT) |
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| Metric | Value | |
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|--------------------------|---------------------------------| |
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| Duration (in seconds) | [More Information Needed] | |
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| Emissions (Co2eq in kg) | [More Information Needed] | |
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| CPU power (W) | [NO CPU] | |
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| GPU power (W) | [No GPU] | |
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| RAM power (W) | [More Information Needed] | |
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| CPU energy (kWh) | [No CPU] | |
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| GPU energy (kWh) | [No GPU] | |
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| RAM energy (kWh) | [More Information Needed] | |
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| Consumed energy (kWh) | [More Information Needed] | |
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| Country name | [More Information Needed] | |
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| Cloud provider | [No Cloud] | |
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| Cloud region | [No Cloud] | |
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| CPU count | [No CPU] | |
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| CPU model | [No CPU] | |
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| GPU count | [No GPU] | |
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| GPU model | [No GPU] | |
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## Environmental Impact (for one core) |
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| Metric | Value | |
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|--------------------------|---------------------------------| |
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| CPU energy (kWh) | [No CPU] | |
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| Emissions (Co2eq in kg) | [More Information Needed] | |
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## Note |
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2 May 2024 |
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## My Config |
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| Config | Value | |
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|--------------------------|-----------------| |
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| checkpoint | albert-base-v2 | |
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| model_name | BERTrand_bs16_lr5_MLM | |
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| sequence_length | 400 | |
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| num_epoch | 12 | |
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| learning_rate | 5e-05 | |
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| batch_size | 16 | |
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| weight_decay | 0.0 | |
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| warm_up_prop | 0 | |
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| drop_out_prob | 0.1 | |
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| packing_length | 100 | |
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| train_test_split | 0.2 | |
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| num_steps | 13033 | |
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## Training and Testing steps |
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Epoch | Train Loss | Test Loss |
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---|---|--- |
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| 0.0 | 14.743229 | 13.097182 | |
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| 0.5 | 7.100540 | 6.967106 | |
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| 1.0 | 6.948475 | 6.939338 | |
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| 1.5 | 6.938035 | 6.938765 | |
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| 2.0 | 6.931950 | 6.935680 | |
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| 2.5 | 6.923858 | 6.936854 | |
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| 3.0 | 6.920174 | 6.932032 | |
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| 3.5 | 6.920139 | 6.914489 | |
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| 4.0 | 6.911595 | 6.913473 | |
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| 4.5 | 6.905194 | 6.909112 | |
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| 5.0 | 6.903432 | 6.907618 | |
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| 5.5 | 6.901336 | 6.901513 | |
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| 6.0 | 6.896765 | 6.905171 | |
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| 6.5 | 6.900726 | 6.894976 | |
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| 7.0 | 6.881094 | 6.894709 | |
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| 7.5 | 6.885156 | 6.894880 | |
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| 8.0 | 6.883777 | 6.893790 | |
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| 8.5 | 6.884839 | 6.888695 | |
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| 9.0 | 6.881206 | 6.888314 | |
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| 9.5 | 6.875793 | 6.884028 | |
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| 10.0 | 6.871364 | 6.881168 | |
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| 10.5 | 6.880161 | 6.887640 | |
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| 11.0 | 6.878505 | 6.883618 | |
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| 11.5 | 6.873283 | 6.881647 | |
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