sentiment analysis (UGC) heBERT oscar-based v0.1
Browse files- config.json +5 -5
- pytorch_model.bin +2 -2
- training_args.bin +2 -2
- vocab.txt +0 -0
config.json
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@@ -20,12 +20,12 @@
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"possitive": 1
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},
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"layer_norm_eps": 1e-12,
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"max_position_embeddings":
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"model_type": "bert",
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"num_attention_heads": 12,
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"num_hidden_layers":
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"pad_token_id": 0,
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"total_flos":
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"type_vocab_size":
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"vocab_size":
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}
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"possitive": 1
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},
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"layer_norm_eps": 1e-12,
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+
"max_position_embeddings": 512,
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"model_type": "bert",
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"num_attention_heads": 12,
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"num_hidden_layers": 12,
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"pad_token_id": 0,
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"total_flos": 6997313242916978688,
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"type_vocab_size": 2,
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"vocab_size": 30522
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}
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size
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version https://git-lfs.github.com/spec/v1
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oid sha256:a77af041ae166db845c326be483417c7b9a44391fed8b53c394384d9d6908997
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size 438027135
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training_args.bin
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@@ -1,3 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size
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version https://git-lfs.github.com/spec/v1
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oid sha256:f0d54091151d41e2c8f2c6c12662d8c3a62fd9a6014924d5b1eff972fa1b9177
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size 1775
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vocab.txt
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