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bert2bert-no-cross-attn-decoder
GItaf/bert2bert-no-cross-attn-decoder
bert2bert-no-cross-attn-decoder is a text generation model from GItaf. Use it when you need the model to write or continue 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 Generation
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- Sep 5, 2022
- Updated
- Sep 8, 2022
- SHA
- 996ef859
Try a prompt
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-uncased-bert-base-uncased-finetuned-mbti-0909
This model is a fine-tuned version of on the None dataset. It achieves the following results on the evaluation set:
- Loss: 6.0549
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: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 5.2244 | 1.0 | 1735 | 5.7788 |
| 4.8483 | 2.0 | 3470 | 5.7647 |
| 4.7578 | 3.0 | 5205 | 5.9016 |
| 4.5606 | 4.0 | 6940 | 5.9895 |
| 4.4314 | 5.0 | 8675 | 6.0549 |
Framework versions
- Transformers 4.21.2
- Pytorch 1.12.1
- Datasets 2.4.0
- Tokenizers 0.12.1
- Task
- Text Generation
- Library
- transformers
- Type
- bert
- Created
- Sep 5, 2022
- Updated
- Sep 8, 2022