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RPA_Synth1_ON_7_Nov
am-infoweb/RPA_Synth1_ON_7_Nov
RPA_Synth1_ON_7_Nov 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 6, 2023
- Updated
- Nov 6, 2023
- SHA
- 1611ee8d
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_Synth1_ON_7_Nov
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: 3
- eval_batch_size: 3
- 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 |
|---|---|---|---|
| 1.2413 | 1.0 | 825 | 0.0210 |
| 0.034 | 2.0 | 1650 | 0.0023 |
| 0.025 | 3.0 | 2475 | 0.0009 |
| 0.007 | 4.0 | 3300 | 0.0005 |
| 0.012 | 5.0 | 4125 | 0.0084 |
| 0.0087 | 6.0 | 4950 | 0.0000 |
| 0.0009 | 7.0 | 5775 | 0.0001 |
| 0.0 | 8.0 | 6600 | 0.0000 |
| 0.0035 | 9.0 | 7425 | 0.0000 |
| 0.0 | 10.0 | 8250 | 0.0000 |
| 0.0085 | 11.0 | 9075 | 0.0000 |
| 0.0 | 12.0 | 9900 | 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 6, 2023
- Updated
- Nov 6, 2023