Environmental Impact (CODE CARBON DEFAULT)
| Metric | Value |
|---|---|
| Duration (in seconds) | 133400.54946255684 |
| Emissions (Co2eq in kg) | 0.1003578773584826 |
| CPU power (W) | 42.5 |
| GPU power (W) | [No GPU] |
| RAM power (W) | 15.0 |
| CPU energy (kWh) | 1.5748644854989302 |
| GPU energy (kWh) | [No GPU] |
| RAM energy (kWh) | 0.5558307727436196 |
| Consumed energy (kWh) | 2.1306952582425556 |
| Country name | Switzerland |
| Cloud provider | nan |
| Cloud region | nan |
| CPU count | 6 |
| 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) | 0.2567960577154219 |
| Emissions (Co2eq in kg) | 0.05224854853950143 |
Note
5 juillet 2024 !
My Config
| Config | Value |
|---|---|
| checkpoint | albert-base-v2 |
| model_name | fp_bs64_lr2e4_x8 |
| sequence_length | 400 |
| num_epoch | 6 |
| learning_rate | 0.0002 |
| batch_size | 64 |
| weight_decay | 0.0 |
| warm_up_prop | 0.0 |
| drop_out_prob | 0.1 |
| packing_length | 100 |
| train_test_split | 0.2 |
| num_steps | 10293 |
Training and Testing steps
| Epoch | Train Loss | Test Loss |
|---|---|---|
| 0.0 | 15.906882 | 12.832661 |
| 0.5 | 7.092607 | 6.999419 |
| 1.0 | 6.981287 | 6.986191 |
| 1.5 | 6.967905 | 6.977545 |
| 2.0 | 6.967524 | 6.969170 |
| 2.5 | 6.958081 | 6.965345 |
| 3.0 | 6.949910 | 6.963099 |
| 3.5 | 6.946939 | 6.961284 |
| 4.0 | 6.944817 | 6.953704 |
| 4.5 | 6.950408 | 6.947729 |
| 5.0 | 6.943814 | 6.941078 |
| 5.5 | 6.932719 | 6.937982 |
| 6.0 | 6.924235 | 6.939940 |
- Downloads last month
- 6
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.