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RPA_Synth_08nov
am-infoweb/RPA_Synth_08nov
RPA_Synth_08nov is a question answering model from am-infoweb. Use it when the input is a question plus a passage. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Question Answering
- Library
- transformers
- License
- mit
- Model type
- xlm-roberta
- Access
- Public
- Created
- Nov 7, 2023
- Updated
- Nov 7, 2023
- SHA
- d69f2f2b
Try a prompt
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. -->
RPA_Synth_08nov
This model is a fine-tuned version of xlm-roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0000
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: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 12
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.6252 | 1.0 | 928 | 0.0001 |
| 0.0576 | 2.0 | 1856 | 0.0002 |
| 0.0541 | 3.0 | 2784 | 0.0000 |
| 0.0151 | 4.0 | 3712 | 0.0000 |
| 0.0251 | 5.0 | 4640 | 0.0031 |
| 0.0343 | 6.0 | 5568 | 0.0000 |
| 0.0263 | 7.0 | 6496 | 0.0002 |
| 0.009 | 8.0 | 7424 | 0.0000 |
| 0.0149 | 9.0 | 8352 | 0.0000 |
| 0.0068 | 10.0 | 9280 | 0.0000 |
| 0.0065 | 11.0 | 10208 | 0.0000 |
| 0.0037 | 12.0 | 11136 | 0.0000 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.0.1
- Datasets 2.14.6
- Tokenizers 0.14.1
- Task
- Question Answering
- Library
- transformers
- Type
- xlm-roberta
- License
- mit
- Created
- Nov 7, 2023
- Updated
- Nov 7, 2023