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bert2bert_shared-spanish-finetuned-summarization-intento2
EP9/bert2bert_shared-spanish-finetuned-summarization-intento2
bert2bert_shared-spanish-finetuned-summarization-intento2 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 23, 2022
- Updated
- Nov 23, 2022
- SHA
- 6e7e2cd3
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-intento2
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: 7.9693
- Rouge1: 1.8257
- Rouge2: 0.0
- Rougel: 1.6832
- Rougelsum: 1.6866
- Gen Len: 10.0
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: 8
- eval_batch_size: 8
- 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 |
|---|---|---|---|---|---|---|---|---|
| 7.9999 | 1.0 | 6180 | 7.9915 | 1.5443 | 0.0 | 1.4357 | 1.4377 | 10.0 |
| 7.9469 | 2.0 | 12360 | 7.9693 | 1.8257 | 0.0 | 1.6832 | 1.6866 | 10.0 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.12.1+cu113
- Datasets 2.7.1
- Tokenizers 0.13.2
- Library
- transformers
- Type
- encoder-decoder
- Created
- Nov 23, 2022
- Updated
- Nov 23, 2022