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bert2bert_shared-spanish-finetuned-summarization-finetuned-xsum
EP9/bert2bert_shared-spanish-finetuned-summarization-finetuned-xsum
bert2bert_shared-spanish-finetuned-summarization-finetuned-xsum is a machine learning model from EP9. 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
- Nov 20, 2022
- Updated
- Nov 21, 2022
- SHA
- d3359716
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. -->
bert2bert_shared-spanish-finetuned-summarization-finetuned-xsum
This model is a fine-tuned version of mrm8488/bert2bert_shared-spanish-finetuned-summarization on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.3690
- Rouge1: 50.02
- Rouge2: 35.706
- Rougel: 46.6253
- Rougelsum: 46.6412
- Gen Len: 22.1176
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: 16
- eval_batch_size: 16
- 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 | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 2.5969 | 1.0 | 3090 | 2.4559 | 49.4282 | 35.2705 | 46.095 | 46.0994 | 22.5422 |
| 2.3318 | 2.0 | 6180 | 2.3690 | 50.02 | 35.706 | 46.6253 | 46.6412 | 22.1176 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.12.1+cu113
- Datasets 2.7.0
- Tokenizers 0.13.2
- Library
- transformers
- Type
- encoder-decoder
- Created
- Nov 20, 2022
- Updated
- Nov 21, 2022