Update Hallucination README.md
* Update README.md
* Update retrievers.py
Raise AssertionError when `NaN` values appear.
* Update README.md
slightly add more instructions to the readme file in RAG
* Revert "Update README.md"
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* Revert "Update retrievers.py"
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* merge master
@@ -87,6 +87,7 @@ The following commands demonstrate how to train some of the models above; we int
--model-parallel True --optimizer adam --text-truncate 512 --truncate 512 \
--learningrate 1e-05 --validation-metric-mode min --validation-every-n-epochs 0.25 \
--validation-max-exs 1000 --validation-metric ppl --validation-patience 5 \
+ --model-file /path/to/saved/model
#### Train a T5-Large RAG-Turn Doc-Then-Turn model with DPR Retrieval on WoW
@@ -98,6 +99,7 @@ The following commands demonstrate how to train some of the models above; we int
--model-parallel True --optimizer adam --text-truncate 512 --truncate 512 \
--learningrate 1e-05 --validation-metric-mode min --validation-every-n-epochs 0.25 \
--validation-max-exs 1000 --validation-metric ppl --validation-patience 5 \
+ --model-file /path/to/saved/model
#### Train a BlenderBot-2.7B RAG Sequence Model with DPR-Poly Retrieval on WoW
@@ -113,6 +115,7 @@ For the BlenderBot model, we add extra positions to the encoder, so that we can
--model-parallel True --optimizer adam \
--learningrate 1e-05 --validation-metric-mode min --validation-every-n-epochs 0.25 \
--validation-max-exs 1000 --validation-metric ppl --validation-patience 5 \
+ --model-file /path/to/saved/model
#### Train a BART-Large FiD Model, with a DPR Retriever initialized from a DPR Model trained with RAG.
@@ -127,6 +130,7 @@ This is the **BART FiD RAG** model specified above.
--model-parallel True --optimizer adam --text-truncate 512 --truncate 512 \
--learningrate 1e-05 --validation-metric-mode min --validation-every-n-epochs 0.25 \
--validation-max-exs 1000 --validation-metric ppl --validation-patience 5 \
+ --model-file /path/to/saved/model
#### Train a T5-Base FiD Model, using a smaller index for debug purposes.
@@ -142,3 +146,4 @@ We provide a smaller FAISS index comprising ~3k documents, which encompasses all
--model-parallel True --optimizer adam --text-truncate 512 --truncate 512 \
--learningrate 1e-05 --validation-metric-mode min --validation-every-n-epochs 0.25 \
--validation-max-exs 1000 --validation-metric ppl --validation-patience 5 \
+ --model-file /path/to/saved/model
