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--- |
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license: apache-2.0 |
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pipeline_tag: question-answering |
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tags: |
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- question-answering |
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- transformers |
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- generated_from_trainer |
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datasets: |
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- squad_v2 |
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- LLukas22/nq-simplified |
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language: |
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- en |
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--- |
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# all-MiniLM-L12-v2-qa-en |
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This model is an extractive qa model. |
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It's a fine-tuned version of [all-MiniLM-L12-v2](https://huggingface.co/sentence-transformers/all-MiniLM-L12-v2) on the following datasets: [squad_v2](https://huggingface.co/datasets/squad_v2), [LLukas22/nq-simplified](https://huggingface.co/datasets/LLukas22/nq-simplified). |
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## Usage |
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You can use the model like this: |
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```python |
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from transformers import pipeline |
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#Make predictions |
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model_name = "LLukas22/all-MiniLM-L12-v2-qa-en" |
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nlp = pipeline('question-answering', model=model_name, tokenizer=model_name) |
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QA_input = { |
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"question": "What's my name?", |
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"context": "My name is Clara and I live in Berkeley." |
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} |
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result = nlp(QA_input) |
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print(result) |
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``` |
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Alternatively you can load the model and tokenizer on their own: |
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```python |
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from transformers import AutoModelForQuestionAnswering, AutoTokenizer |
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#Make predictions |
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model_name = "LLukas22/all-MiniLM-L12-v2-qa-en" |
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model = AutoModelForQuestionAnswering.from_pretrained(model_name) |
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tokenizer = AutoTokenizer.from_pretrained(model_name) |
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``` |
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## Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2E-05 |
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- per device batch size: 60 |
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- effective batch size: 180 |
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- seed: 42 |
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- optimizer: AdamW with betas (0.9,0.999) and eps 1E-08 |
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- weight decay: 1E-02 |
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- D-Adaptation: False |
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- Warmup: False |
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- number of epochs: 10 |
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- mixed_precision_training: bf16 |
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## Training results |
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| Epoch | Train Loss | Validation Loss | |
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| ----- | ---------- | --------------- | |
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| 0 | 2.65 | 1.88 | |
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| 1 | 1.83 | 1.74 | |
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| 2 | 1.69 | 1.69 | |
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| 3 | 1.63 | 1.68 | |
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| 4 | 1.6 | 1.67 | |
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| 5 | 1.58 | 1.66 | |
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| 6 | 1.57 | 1.66 | |
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| 7 | 1.57 | 1.66 | |
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## Evaluation results |
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| Epoch | f1 | exact_match | |
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| ----- | ----- | ----- | |
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| 0 | 0.507 | 0.378 | |
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| 1 | 0.53 | 0.418 | |
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| 2 | 0.544 | 0.431 | |
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| 3 | 0.552 | 0.429 | |
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| 4 | 0.557 | 0.439 | |
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| 5 | 0.561 | 0.438 | |
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| 6 | 0.564 | 0.441 | |
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| 7 | 0.566 | 0.441 | |
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## Framework versions |
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- Transformers: 4.25.1 |
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- PyTorch: 2.0.0+cu118 |
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- PyTorch Lightning: 1.8.6 |
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- Datasets: 2.7.1 |
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- Tokenizers: 0.13.1 |
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- Sentence Transformers: 2.2.2 |
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## Additional Information |
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This model was trained as part of my Master's Thesis **'Evaluation of transformer based language models for use in service information systems'**. The source code is available on [Github](https://github.com/LLukas22/Retrieval-Augmented-QA). |
