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distilbert-base-uncased_fold_13_binary_v1
elopezlopez/distilbert-base-uncased_fold_13_binary_v1
distilbert-base-uncased_fold_13_binary_v1 is a text classification model from elopezlopez. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- distilbert
- Access
- Public
- Created
- Aug 3, 2022
- Updated
- Aug 3, 2022
- SHA
- c8d30cee
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Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
distilbert-base-uncased_fold_13_binary_v1
This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.7433
- F1: 0.8138
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 25
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|---|---|---|---|---|
| No log | 1.0 | 291 | 0.4101 | 0.8087 |
| 0.4128 | 2.0 | 582 | 0.4605 | 0.8197 |
| 0.4128 | 3.0 | 873 | 0.5011 | 0.8130 |
| 0.1997 | 4.0 | 1164 | 0.6882 | 0.8147 |
| 0.1997 | 5.0 | 1455 | 0.9653 | 0.8092 |
| 0.0913 | 6.0 | 1746 | 1.1020 | 0.8031 |
| 0.0347 | 7.0 | 2037 | 1.2687 | 0.8050 |
| 0.0347 | 8.0 | 2328 | 1.2383 | 0.8103 |
| 0.0173 | 9.0 | 2619 | 1.3631 | 0.8066 |
| 0.0173 | 10.0 | 2910 | 1.4282 | 0.8001 |
| 0.0104 | 11.0 | 3201 | 1.4410 | 0.8179 |
| 0.0104 | 12.0 | 3492 | 1.5318 | 0.8018 |
| 0.0063 | 13.0 | 3783 | 1.5866 | 0.8018 |
| 0.0043 | 14.0 | 4074 | 1.4987 | 0.8159 |
| 0.0043 | 15.0 | 4365 | 1.6275 | 0.8181 |
| 0.0048 | 16.0 | 4656 | 1.5811 | 0.8231 |
| 0.0048 | 17.0 | 4947 | 1.6228 | 0.8182 |
| 0.0048 | 18.0 | 5238 | 1.7235 | 0.8138 |
| 0.0055 | 19.0 | 5529 | 1.7018 | 0.8066 |
| 0.0055 | 20.0 | 5820 | 1.7340 | 0.8069 |
| 0.0046 | 21.0 | 6111 | 1.7143 | 0.8156 |
| 0.0046 | 22.0 | 6402 | 1.7367 | 0.8159 |
| 0.0037 | 23.0 | 6693 | 1.7551 | 0.8151 |
| 0.0037 | 24.0 | 6984 | 1.7479 | 0.8145 |
| 0.0009 | 25.0 | 7275 | 1.7433 | 0.8138 |
Framework versions
- Transformers 4.21.0
- Pytorch 1.12.0+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- Aug 3, 2022
- Updated
- Aug 3, 2022