Commit ·
902b2a4
1
Parent(s): 279848f
fixed a description error in README
Browse files
README.md
CHANGED
|
@@ -43,7 +43,7 @@ We used the following corpora for pre-training:
|
|
| 43 |
We first segmented texts in the corpora into words using [Juman++](https://github.com/ku-nlp/jumanpp).
|
| 44 |
Then, we built a sentencepiece model with 32000 tokens including words ([JumanDIC](https://github.com/ku-nlp/JumanDIC)) and subwords induced by the unigram language model of [sentencepiece](https://github.com/google/sentencepiece).
|
| 45 |
|
| 46 |
-
We tokenized the segmented corpora into subwords using the sentencepiece model and trained the Japanese BART model using [
|
| 47 |
The training took 2 weeks using 4 Tesla V100 GPUs.
|
| 48 |
|
| 49 |
The following hyperparameters were used during pre-training:
|
|
|
|
| 43 |
We first segmented texts in the corpora into words using [Juman++](https://github.com/ku-nlp/jumanpp).
|
| 44 |
Then, we built a sentencepiece model with 32000 tokens including words ([JumanDIC](https://github.com/ku-nlp/JumanDIC)) and subwords induced by the unigram language model of [sentencepiece](https://github.com/google/sentencepiece).
|
| 45 |
|
| 46 |
+
We tokenized the segmented corpora into subwords using the sentencepiece model and trained the Japanese BART model using [fairseq](https://github.com/facebookresearch/fairseq) library.
|
| 47 |
The training took 2 weeks using 4 Tesla V100 GPUs.
|
| 48 |
|
| 49 |
The following hyperparameters were used during pre-training:
|