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bert-small2bert-small-finetuned-cnn_daily_mail-summarization-newsroom-filtered
keith97/bert-small2bert-small-finetuned-cnn_daily_mail-summarization-newsroom-filtered
bert-small2bert-small-finetuned-cnn_daily_mail-summarization-newsroom-filtered is a machine learning model from keith97. 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. 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
- Library
- transformers
- License
- apache-2.0
- Model type
- encoder-decoder
- Access
- Public
- Created
- Nov 6, 2022
- Updated
- Nov 6, 2022
- SHA
- 817f3766
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-small2bert-small-finetuned-cnn_daily_mail-summarization-newsroom-filtered
This model is a fine-tuned version of mrm8488/bert-small2bert-small-finetuned-cnn_daily_mail-summarization on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 3.5413
- Rouge1: 32.3232
- Rouge2: 20.9203
- Rougel: 27.232
- Rougelsum: 29.345
- Gen Len: 72.2217
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
- lr_scheduler_warmup_steps: 500
- num_epochs: 5
- mixed_precision_training: Native AMP
- label_smoothing_factor: 0.1
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 3.796 | 0.89 | 405 | 3.6945 | 29.7168 | 17.6705 | 24.4204 | 26.484 | 69.6847 |
| 3.6426 | 1.78 | 810 | 3.5532 | 32.3051 | 20.8789 | 27.1724 | 29.384 | 72.3695 |
| 3.2645 | 2.66 | 1215 | 3.5437 | 32.2016 | 20.758 | 27.083 | 29.0954 | 73.3892 |
| 3.1719 | 3.55 | 1620 | 3.5377 | 32.5493 | 21.083 | 27.0881 | 29.4691 | 71.5222 |
| 2.9763 | 4.44 | 2025 | 3.5413 | 32.3232 | 20.9203 | 27.232 | 29.345 | 72.2217 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.11.0
- Datasets 2.1.0
- Tokenizers 0.12.1
- Library
- transformers
- Type
- encoder-decoder
- License
- apache-2.0
- Created
- Nov 6, 2022
- Updated
- Nov 6, 2022