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QA_FineTuned
gp-tar4/QA_FineTuned
QA_FineTuned is a question answering model from gp-tar4. Use it when the input is a question plus a passage. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Question Answering
- Library
- transformers
- Model type
- electra
- Access
- Public
- Created
- Apr 28, 2024
- Updated
- Apr 29, 2024
- SHA
- 05b3b432
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. -->
QA_FineTuned_Arabert
This model is a fine-tuned version of zohaib99k/Bert_Arabic-SQuADv2-QA on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 3.3343
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: 0.0002
- train_batch_size: 12
- eval_batch_size: 12
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 48
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.1603 | 0.46 | 10 | 2.7965 |
| 0.3055 | 0.92 | 20 | 3.0322 |
| 0.3091 | 1.38 | 30 | 2.8940 |
| 0.2692 | 1.84 | 40 | 2.9621 |
| 0.2198 | 2.3 | 50 | 2.9107 |
| 0.2112 | 2.76 | 60 | 3.1322 |
| 0.1576 | 3.22 | 70 | 3.2085 |
| 0.1392 | 3.68 | 80 | 3.1323 |
| 0.1474 | 4.14 | 90 | 3.2893 |
| 0.0905 | 4.6 | 100 | 3.3343 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2
- Task
- Question Answering
- Library
- transformers
- Type
- electra
- Languages
- ar
- Created
- Apr 28, 2024
- Updated
- Apr 29, 2024