Add config.json

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+config.json filter=lfs diff=lfs merge=lfs -text

.ipynb_checkpoints/README-checkpoint.md

@@ -0,0 +1,13 @@
+---
+license: mit
+language:
+- ja
+tags:
+- PyTorch
+- Transformers
+---
+
+Japanese Stock Comment Sentiment Model
+
+This model is a sentiment analysis tool specifically trained to analyze comments and discussions related to Japanese stocks. It is specialized in determining whether a comment has a bearish or bullish sentiment.
+For its training, a large collection of individual stock-related comments was gathered, and these were categorized into two main categories: "bullish" and "bearish." This model can serve as a supportive tool for stock investors and market analysts in gathering information and making prompt decisions.

config.json

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c271b07279966955f9d386b440b0968ab195f55a71791df755f1489bcf89c4c6
+size 870

special_tokens_map.json

@@ -0,0 +1,7 @@
+{
+  "cls_token": "[CLS]",
+  "mask_token": "[MASK]",
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "unk_token": "[UNK]"
+}

tokenizer_config.json

@@ -0,0 +1,18 @@
+{
+  "cls_token": "[CLS]",
+  "do_lower_case": false,
+  "do_subword_tokenize": true,
+  "do_word_tokenize": true,
+  "mask_token": "[MASK]",
+  "mecab_kwargs": null,
+  "model_max_length": 512,
+  "name_or_path": "cl-tohoku/bert-base-japanese-whole-word-masking",
+  "never_split": null,
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "special_tokens_map_file": null,
+  "subword_tokenizer_type": "wordpiece",
+  "tokenizer_class": "BertJapaneseTokenizer",
+  "unk_token": "[UNK]",
+  "word_tokenizer_type": "mecab"
+}

training_args.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:78cf65f3982a45acc196317ec75f56eded3f073acdcdc5e7255b59130b128d7a
+size 3311