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results_distilbert-base-uncased
Mbabazi/results_distilbert-base-uncased
results_distilbert-base-uncased is a text classification model from Mbabazi. 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
- Nov 1, 2023
- Updated
- Nov 2, 2023
- SHA
- 99a67e56
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Base models
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. -->
results_distilbert-base-uncased
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3782
- Accuracy: 0.744
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: 1e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 600
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.6859 | 0.12 | 30 | 0.6867 | 0.304 |
| 0.6759 | 0.24 | 60 | 0.6723 | 0.3535 |
| 0.6508 | 0.36 | 90 | 0.6433 | 0.43 |
| 0.6046 | 0.48 | 120 | 0.5999 | 0.4915 |
| 0.5845 | 0.6 | 150 | 0.5733 | 0.491 |
| 0.579 | 0.72 | 180 | 0.5633 | 0.6455 |
| 0.5599 | 0.84 | 210 | 0.5484 | 0.5705 |
| 0.526 | 0.96 | 240 | 0.5208 | 0.679 |
| 0.4968 | 1.08 | 270 | 0.4765 | 0.7115 |
| 0.4763 | 1.2 | 300 | 0.4524 | 0.7165 |
| 0.4565 | 1.32 | 330 | 0.4341 | 0.7205 |
| 0.4345 | 1.44 | 360 | 0.4254 | 0.7235 |
| 0.4338 | 1.56 | 390 | 0.4161 | 0.73 |
| 0.4292 | 1.68 | 420 | 0.4119 | 0.729 |
| 0.4129 | 1.8 | 450 | 0.4061 | 0.7345 |
| 0.4036 | 1.92 | 480 | 0.3966 | 0.739 |
| 0.4019 | 2.04 | 510 | 0.3984 | 0.726 |
| 0.3794 | 2.16 | 540 | 0.3961 | 0.74 |
| 0.3756 | 2.28 | 570 | 0.3981 | 0.728 |
| 0.4565 | 2.4 | 600 | 0.3903 | 0.73 |
| 0.376 | 2.52 | 630 | 0.3997 | 0.7285 |
| 0.4023 | 2.64 | 660 | 0.3850 | 0.7435 |
| 0.3511 | 2.76 | 690 | 0.3802 | 0.742 |
| 0.3601 | 2.88 | 720 | 0.3782 | 0.744 |
| 0.3771 | 3.0 | 750 | 0.3792 | 0.742 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- Nov 1, 2023
- Updated
- Nov 2, 2023