# Load model directly
from transformers import AutoTokenizer, AutoModelForQuestionAnswering
tokenizer = AutoTokenizer.from_pretrained("StaAhmed/Values_QA")
model = AutoModelForQuestionAnswering.from_pretrained("StaAhmed/Values_QA")Quick Links
Values_QA
This model is a fine-tuned version of StaAhmed/my_awesome_qa_model on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.7953
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: 16
- eval_batch_size: 16
- 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 |
|---|---|---|---|
| No log | 1.0 | 9 | 2.6667 |
| No log | 2.0 | 18 | 2.3185 |
| No log | 3.0 | 27 | 1.9446 |
| No log | 4.0 | 36 | 1.7909 |
| No log | 5.0 | 45 | 1.7953 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="StaAhmed/Values_QA")