Downloads · 30 days
7
22% of all-time downloads
distilbert_sa_GLUE_Experiment_logit_kd_data_aug_mrpc_256
gokuls/distilbert_sa_GLUE_Experiment_logit_kd_data_aug_mrpc_256
distilbert_sa_GLUE_Experiment_logit_kd_data_aug_mrpc_256 is a text classification model from gokuls. 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. --
All-time downloads
32
Public
Repo size
686 MB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.bin76.3 MB · 99%
At a glance
- Task
- Text Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- distilbert
- Access
- Public
- Created
- Feb 4, 2023
- Updated
- Feb 4, 2023
- SHA
- b68b4473
Try a prompt
Datasets
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_sa_GLUE_Experiment_logit_kd_data_aug_mrpc_256
This model is a fine-tuned version of distilbert-base-uncased on the GLUE MRPC dataset. It achieves the following results on the evaluation set:
- Loss: 0.3967
- Accuracy: 0.9902
- F1: 0.9928
- Combined Score: 0.9915
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: 5e-05
- train_batch_size: 256
- eval_batch_size: 256
- seed: 10
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Combined Score |
|---|---|---|---|---|---|---|
| 0.4491 | 1.0 | 980 | 0.4030 | 0.9632 | 0.9727 | 0.9680 |
| 0.4186 | 2.0 | 1960 | 0.4002 | 0.9730 | 0.9800 | 0.9765 |
| 0.4153 | 3.0 | 2940 | 0.3983 | 0.9926 | 0.9946 | 0.9936 |
| 0.4139 | 4.0 | 3920 | 0.3967 | 0.9902 | 0.9928 | 0.9915 |
| 0.413 | 5.0 | 4900 | 0.3968 | 1.0 | 1.0 | 1.0 |
| 0.4125 | 6.0 | 5880 | 0.3970 | 0.9877 | 0.9910 | 0.9894 |
| 0.4121 | 7.0 | 6860 | 0.3971 | 1.0 | 1.0 | 1.0 |
| 0.4118 | 8.0 | 7840 | 0.3968 | 0.9926 | 0.9946 | 0.9936 |
| 0.4116 | 9.0 | 8820 | 0.3968 | 0.9951 | 0.9964 | 0.9958 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.9.0
- Tokenizers 0.13.2
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Languages
- en
- Created
- Feb 4, 2023
- Updated
- Feb 4, 2023