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bert-small-finetuned-eurlex-longer
muhtasham/bert-small-finetuned-eurlex-longer
bert-small-finetuned-eurlex-longer is a fill-mask model from muhtasham. Use it when you need the model to fill a missing word. 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
- Task
- Fill-Mask
- Library
- transformers
- License
- apache-2.0
- Model type
- bert
- Access
- Public
- Created
- Aug 14, 2022
- Updated
- Sep 13, 2023
- SHA
- 5e3f4688
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Base models
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_uncased_L-4_H-512_A-8-finetuned-eurlex-longer
This model is a fine-tuned version of google/bert_uncased_L-4_H-512_A-8 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.8229
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: 64
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.0308 | 1.0 | 3913 | 0.9303 |
| 1.0053 | 2.0 | 7826 | 0.9066 |
| 0.9799 | 3.0 | 11739 | 0.8795 |
| 0.9575 | 4.0 | 15652 | 0.8677 |
| 0.9413 | 5.0 | 19565 | 0.8555 |
| 0.9319 | 6.0 | 23478 | 0.8447 |
| 0.9235 | 7.0 | 27391 | 0.8388 |
| 0.9132 | 8.0 | 31304 | 0.8345 |
| 0.9105 | 9.0 | 35217 | 0.8312 |
| 0.9154 | 10.0 | 39130 | 0.8229 |
Framework versions
- Transformers 4.21.1
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
- Task
- Fill-Mask
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Aug 14, 2022
- Updated
- Sep 13, 2023