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distilbert_lda_5_v1_qnli
gokulsrinivasagan/distilbert_lda_5_v1_qnli
distilbert_lda_5_v1_qnli is a text classification model from gokulsrinivasagan. Use it when you need a label for a piece of text. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- distilbert
- Access
- Public
- Created
- Nov 26, 2024
- Updated
- Dec 4, 2024
- SHA
- b41531d5
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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_lda_5_v1_qnli
This model is a fine-tuned version of gokulsrinivasagan/distilbert_lda_5_v1 on the GLUE QNLI dataset. It achieves the following results on the evaluation set:
- Loss: 0.3706
- Accuracy: 0.8435
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
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 50
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.497 | 1.0 | 410 | 0.3871 | 0.8303 |
| 0.3635 | 2.0 | 820 | 0.3706 | 0.8435 |
| 0.2745 | 3.0 | 1230 | 0.3750 | 0.8376 |
| 0.1968 | 4.0 | 1640 | 0.4567 | 0.8309 |
| 0.1394 | 5.0 | 2050 | 0.5239 | 0.8321 |
| 0.1001 | 6.0 | 2460 | 0.5522 | 0.8342 |
| 0.0764 | 7.0 | 2870 | 0.6610 | 0.8122 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.2.1+cu118
- Datasets 2.17.0
- Tokenizers 0.20.3
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- Languages
- en
- Created
- Nov 26, 2024
- Updated
- Dec 4, 2024