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ft_1_14e6_x4
damgomz/ft_1_14e6_x4
ft_1_14e6_x4 is a text classification model from damgomz. Use it when you need a label for a piece of text. It is set up for transformers.
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377
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32.9M
5.3 GB on disk
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Repo makeup
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.safetensors132 MB · 98%
At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- albert
- Access
- Public
- Created
- Jun 19, 2024
- Updated
- Jul 14, 2024
- SHA
- babe5ef1
Try a prompt
Model card
From the Hugging Face model README
Environmental Impact (CODE CARBON DEFAULT)
| Metric | Value |
|---|---|
| Duration (in seconds) | 142396.17252278328 |
| Emissions (Co2eq in kg) | 0.0861660715467719 |
| CPU power (W) | 42.5 |
| GPU power (W) | [No GPU] |
| RAM power (W) | 3.75 |
| CPU energy (kWh) | 1.6810618259739525 |
| GPU energy (kWh) | [No GPU] |
| RAM energy (kWh) | 0.1483276041182382 |
| Consumed energy (kWh) | 1.8293894300921836 |
| 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) | 0.27411263210635783 |
| Emissions (Co2eq in kg) | 0.055771834238090116 |
Note
12 juillet 2024
My Config
| Config | Value |
|---|---|
| checkpoint | damgomz/fp_bs32_lr1e4_x4 |
| model_name | ft_1_14e6_x4 |
| sequence_length | 400 |
| num_epoch | 6 |
| learning_rate | 1.4e-05 |
| batch_size | 1 |
| 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 | 0.715121 | 0.503196 |
| 1 | 0.265504 | 0.228278 | 0.930515 |
| 2 | 0.170027 | 0.220458 | 0.936902 |
| 3 | 0.103139 | 0.245753 | 0.899291 |
| 4 | 0.051522 | 0.316955 | 0.921900 |
| 5 | 0.024985 | 0.410097 | 0.913188 |
| 6 | 0.014898 | 0.408796 | 0.924605 |
- Task
- Text Classification
- Library
- transformers
- Type
- albert
- Languages
- en
- Created
- Jun 19, 2024
- Updated
- Jul 14, 2024