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pytorch_model.bin2b9d764bb07ec13b33229906d220eeb86135b143a6a532955e6e3f2c194b9754
tokenizer.jsonbcc8903874b133941b537f7db855c20b5b792986bb08b32868afd0a3d593a042
spm.model13c8d666d62a7bc4ac8f040aab68e942c861f93303156cc28f5c7e885d86d6e3
training_args.bin40b8986c384ce4afbb04d0ea5ec3af2ae53b4349844d744382938899fe37e2d4
.gitattributesSHA-256 not recorded
tokenizer_config.jsonSHA-256 not recorded
config.jsonSHA-256 not recorded
special_tokens_map.jsonSHA-256 not recorded
README.mdSHA-256 not recorded
added_tokens.jsonSHA-256 not recorded
Multilingual mDeBERTa base model fineted on Text_emotions dataset.
Dataset link : https://www.kaggle.com/datasets/nelgiriyewithana/emotions/data
Finetuned for classifying text into sadness (0) joy (1) love (2) anger (3) fear (4) and surprise (5) emotions.
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