|
|
@@ -88,6 +88,7 @@ By default, `prep.py` will make one pass through the text file to compute a
|
|
|
co-occurrence statistics. The following options allow you to control this
|
|
|
behavior:
|
|
|
|
|
|
+| Option | Description |
|
|
|
|:--- |:--- |
|
|
|
| `--min_count <n>` | Only include words in the generated vocabulary that appear at least *n* times. |
|
|
|
| `--max_vocab <n>` | Admit at most *n* words into the vocabulary. |
|
|
|
@@ -115,6 +116,7 @@ that the Swivel trainer needs to run. Train embeddings as follows:
|
|
|
There are a variety of parameters that you can fiddle with to customize the
|
|
|
embeddings; some that you may want to experiment with include:
|
|
|
|
|
|
+| Option | Description |
|
|
|
|:--- |:--- |
|
|
|
| `--embedding_size <dim>` | The dimensionality of the embeddings that are created. By default, 300 dimensional embeddings are created. |
|
|
|
| `--num_epochs <n>` | The number of iterations through the data that are performed. By default, 40 epochs are trained. |
|
Chris Waterson