Fine tune and evaluate transformer model on facebook's bAbi tasks.
> [Towards AI-Complete Question Answering: A Set of Prerequisite Toy Tasks](https://arxiv.org/abs/1502.05698)

Training Code: [p208p2002/bAbi-tasks-with-transformer-model](https://github.com/p208p2002/bAbi-tasks-with-transformer-model)

|task_no|task_name             |score|
|-------|----------------------|-----|
|qa1    |single-supporting-fact|100  |
|qa2    |two-supporting-facts  |99.4 |
|qa3    |three-supporting-facts|62.0 |
|qa4    |two-arg-relations     |100  |
|qa5    |three-arg-relations   |96.5 |
|qa6    |yes-no-questions      |100  |
|qa7    |counting              |100  |
|qa8    |lists-sets            |99.8 |
|qa9    |simple-negation       |100  |
|qa10   | indefinite-knowledge |100  |
|qa11   | basic-coreference    |100  |
|qa12   | conjunction          |100  |
|qa13   | compound-coreference |100  |
|qa14   | time-reasoning       |100  |
|qa15   | basic-deduction      |100  |
|qa16   | basic-induction      |100  |
|qa17   | positional-reasoning |100  |
|qa18   | size-reasoning       |100  |
|qa19   | path-finding         |100  |
|qa20   | agents-motivations   |100  |

```python
# Please use with the follow template

INPUT_TEMPLATE = """
Context:
{context}

Question:
{question}

Answer:
{answer}
"""

input_text = INPUT_TEMPLATE.format_map({
    "context":context,
    "question":question,
    "answer":answer
}).strip()
```
{"datasets": ["facebook/babi_qa"]}
transformers pytorch safetensors gpt2 text-generation dataset:facebook/babi_qa arxiv:1502.05698 autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #safetensors #gpt2 #text-generation #dataset-facebook/babi_qa #arxiv-1502.05698 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

Fine tune and evaluate transformer model on facebook's bAbi tasks.



> 
> Towards AI-Complete Question Answering: A Set of Prerequisite Toy Tasks
> 
> 
> 


Training Code: p208p2002/bAbi-tasks-with-transformer-model


task\_no: qa1, task\_name: single-supporting-fact, score: 100
task\_no: qa2, task\_name: two-supporting-facts, score: 99.4
task\_no: qa3, task\_name: three-supporting-facts, score: 62.0
task\_no: qa4, task\_name: two-arg-relations, score: 100
task\_no: qa5, task\_name: three-arg-relations, score: 96.5
task\_no: qa6, task\_name: yes-no-questions, score: 100
task\_no: qa7, task\_name: counting, score: 100
task\_no: qa8, task\_name: lists-sets, score: 99.8
task\_no: qa9, task\_name: simple-negation, score: 100
task\_no: qa10, task\_name: indefinite-knowledge, score: 100
task\_no: qa11, task\_name: basic-coreference, score: 100
task\_no: qa12, task\_name: conjunction, score: 100
task\_no: qa13, task\_name: compound-coreference, score: 100
task\_no: qa14, task\_name: time-reasoning, score: 100
task\_no: qa15, task\_name: basic-deduction, score: 100
task\_no: qa16, task\_name: basic-induction, score: 100
task\_no: qa17, task\_name: positional-reasoning, score: 100
task\_no: qa18, task\_name: size-reasoning, score: 100
task\_no: qa19, task\_name: path-finding, score: 100
task\_no: qa20, task\_name: agents-motivations, score: 100



TAGS
#transformers #pytorch #safetensors #gpt2 #text-generation #dataset-facebook/babi_qa #arxiv-1502.05698 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
