Merge pull request cgpotts#121 from ryanprince/Minor-spelling-correct…

…ion-

Minor spelling correction.

README.md

@@ -34,7 +34,7 @@ Reference implementations for the `torch_*.py` models, designed to reveal more a
 
 ## `vsm_*` and `hw_wordrelatedness.ipynb`
 
-A until on vector space models of meaning, covering traditional methods like PMI and LSA as well as newer methods like Autoencoders and GloVe. `vsm.py` provides a lot of the core functionality, and `torch_glove.py` and `torch_autoencoder.py` are the learned models that we cover. `vsm_03_retroffiting.ipynb` is an extension that uses `retrofitting.py`, and `vsm_04_contextualreps.ipynb` explores methods for deriving static representations from contextual models.
+A unit on vector space models of meaning, covering traditional methods like PMI and LSA as well as newer methods like Autoencoders and GloVe. `vsm.py` provides a lot of the core functionality, and `torch_glove.py` and `torch_autoencoder.py` are the learned models that we cover. `vsm_03_retroffiting.ipynb` is an extension that uses `retrofitting.py`, and `vsm_04_contextualreps.ipynb` explores methods for deriving static representations from contextual models.
 
 
 ## `sst_*` and `hw_sst.ipynb`

hw_sentiment.ipynb

@@ -428,7 +428,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Here we merge the sotmax and RNN experiments into a single DataFrame:"
+    "Here we merge the softmax and RNN experiments into a single DataFrame:"
    ]
   },
   {
@@ -578,7 +578,7 @@
     "\n",
     "1. Take as inputs (a) a model training wrapper like `fit_softmax_classifier` and (b) an integer `bakeoff_train_size` specifying the number of examples from `bakeoff_dev` that should be included in the train set.\n",
     "1. Split `bakeoff_dev` so that the first `bakeoff_train_size` examples are in the train set and the rest are used for evaluation.\n",
-    "1. Use `sst.experiment` with the user-supplied model training wrapper, `unigram_phi` as defined above, and a train set that consists of SST-3 train and the train portion of `bakeoff_dev` as defined in step 2. The value of `assess_dataframes` should be a list consisting of the SST-3 dev set and the evaluation portion of `bakeoff_dev` as defined in step 2.\n",
+    "1. Use `sst.experiment` with the user-supplied model training wrapper, `unigrams_phi` as defined above, and a train set that consists of SST-3 train and the train portion of `bakeoff_dev` as defined in step 2. The value of `assess_dataframes` should be a list consisting of the SST-3 dev set and the evaluation portion of `bakeoff_dev` as defined in step 2.\n",
     "1. Return the return value of `sst.experiment`.\n",
     "\n",
     "The function `test_run_mixed_training_experiment` will help you iterate to the required design."