@@ -70,9 +70,9 @@ An example on how to use this class is given in the `run_classifier.py` script w
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@@ -70,9 +70,9 @@ An example on how to use this class is given in the `run_classifier.py` script w
### 3. `BertForQuestionAnswering`
### 3. `BertForQuestionAnswering`
`BertForSequenceClassification` is a fine-tuning model that includes `BertModel` with a two-class classifiers on top of the full sequence of last hidden states.
`BertForSequenceClassification` is a fine-tuning model that includes `BertModel` with a tokens classifiers on top of the full sequence of last hidden states.
The token classifier takes as input the full sequence of the last hidden state and compute two scores for each tokens that can for example respectively be the score that a given token is a `start_span`or`end_span` token (see Figures 3c and 3d in the BERT paper).
The tokens classifier takes as input the full sequence of the last hidden state and compute several (e.g. two) scores for each tokens that can for example respectively be the score that a given token is a `start_span`and a`end_span` token (see Figures 3c and 3d in the BERT paper).
An example on how to use this class is given in the `run_squad.py` script which can be used to fine-tune a token classifier using BERT, for example for the SQuAS task.
An example on how to use this class is given in the `run_squad.py` script which can be used to fine-tune a token classifier using BERT, for example for the SQuAS task.
