Instructions to use StaAhmed/Values_QA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use StaAhmed/Values_QA with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("question-answering", model="StaAhmed/Values_QA")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("StaAhmed/Values_QA") model = AutoModelForQuestionAnswering.from_pretrained("StaAhmed/Values_QA", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download README.md from StaAhmed/Values_QA: direct link, hf CLI and curl.
- Browser
- Download file 1.51 kB
-
https://huggingface.co/StaAhmed/Values_QA/resolve/main/README.md
- Command line
-
hf download hf://StaAhmed/Values_QA/README.md
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curl -L -o README.md https://huggingface.co/StaAhmed/Values_QA/resolve/main/README.md
1.51 kB
metadata
license: apache-2.0
base_model: StaAhmed/my_awesome_qa_model
tags:
- generated_from_trainer
model-index:
- name: Values_QA
results: []
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