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bert-base-cnn
harish3742/bert-base-cnn
bert-base-cnn is a machine learning model from harish3742. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- transformers
- Model type
- encoder-decoder
- Access
- Public
- Created
- Apr 5, 2024
- Updated
- Apr 5, 2024
- SHA
- 33a562fa
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-cnn
This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.3839
- Rouge2 Precision: 0.0112
- Rouge2 Recall: 0.0386
- Rouge2 Fmeasure: 0.0162
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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
|---|---|---|---|---|---|---|
| No log | 1.0 | 8 | 1.6622 | 0.0104 | 0.042 | 0.0164 |
| No log | 2.0 | 16 | 1.3839 | 0.0112 | 0.0386 | 0.0162 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
- Library
- transformers
- Type
- encoder-decoder
- Created
- Apr 5, 2024
- Updated
- Apr 5, 2024