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bert_base_lda_100_mrpc
gokulsrinivasagan/bert_base_lda_100_mrpc
bert_base_lda_100_mrpc 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 22, 2024
- Updated
- Nov 22, 2024
- SHA
- 06d642c8
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Base models
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. -->
bert_base_lda_100_mrpc
This model is a fine-tuned version of gokulsrinivasagan/bert_base_lda_100 on the GLUE MRPC dataset. It achieves the following results on the evaluation set:
- Loss: 0.6232
- Accuracy: 0.6838
- F1: 0.8122
- Combined Score: 0.7480
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: 0.001
- 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: 30
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Combined Score |
|---|---|---|---|---|---|---|
| 1.1107 | 1.0 | 15 | 0.7673 | 0.3162 | 0.0 | 0.1581 |
| 0.7425 | 2.0 | 30 | 0.7309 | 0.6838 | 0.8122 | 0.7480 |
| 0.6615 | 3.0 | 45 | 0.6242 | 0.6838 | 0.8122 | 0.7480 |
| 0.6434 | 4.0 | 60 | 0.6252 | 0.6838 | 0.8122 | 0.7480 |
| 0.638 | 5.0 | 75 | 0.6237 | 0.6838 | 0.8122 | 0.7480 |
| 0.6349 | 6.0 | 90 | 0.6238 | 0.6838 | 0.8122 | 0.7480 |
| 0.6359 | 7.0 | 105 | 0.6246 | 0.6838 | 0.8122 | 0.7480 |
| 0.6351 | 8.0 | 120 | 0.6249 | 0.6838 | 0.8122 | 0.7480 |
| 0.6315 | 9.0 | 135 | 0.6337 | 0.6838 | 0.8122 | 0.7480 |
| 0.6373 | 10.0 | 150 | 0.6232 | 0.6838 | 0.8122 | 0.7480 |
| 0.6339 | 11.0 | 165 | 0.6275 | 0.6838 | 0.8122 | 0.7480 |
| 0.6339 | 12.0 | 180 | 0.6240 | 0.6838 | 0.8122 | 0.7480 |
| 0.6318 | 13.0 | 195 | 0.6233 | 0.6838 | 0.8122 | 0.7480 |
| 0.6353 | 14.0 | 210 | 0.6250 | 0.6838 | 0.8122 | 0.7480 |
| 0.6333 | 15.0 | 225 | 0.6246 | 0.6838 | 0.8122 | 0.7480 |
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 22, 2024
- Updated
- Nov 22, 2024