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config.json

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+{
+  "architectures": [
+    "EmoAxis"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "auto_map": {
+    "AutoConfig": "configuration_emoaxis.EmoAxisConfig",
+    "AutoModel": "modeling_emoaxis.EmoAxis"
+  },
+  "bos_token_id": 0,
+  "classifier_dropout": null,
+  "dtype": "float32",
+  "eos_token_id": 2,
+  "freeze_upto": 0,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 514,
+  "model_type": "emoaxis",
+  "num_attention_heads": 12,
+  "num_classes": 28,
+  "num_hidden_layers": 12,
+  "pad_token_id": 1,
+  "position_embedding_type": "absolute",
+  "transformers_version": "4.57.3",
+  "type_vocab_size": 1,
+  "use_cache": true,
+  "vocab_size": 50265
+}

configuration_emoaxis.py

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+from transformers import RobertaConfig
+class EmoAxisConfig(RobertaConfig):
+    model_type = "emoaxis"
+    def __init__(self, num_classes=28, freeze_upto=0, **kwargs):
+        kwargs["max_position_embeddings"] = 514 
+        kwargs["type_vocab_size"] = 1
+        super().__init__(**kwargs)
+        self.num_classes = num_classes
+        self.freeze_upto = freeze_upto

model.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:6c1e18aa9f12900ec531911e9e1563d6e428872e7cf9fa620e542ab2b1ea78ec
+size 497880872

modeling_emoaxis.py

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+import torch
+import torch.nn as nn
+import torch.nn.functional as F
+from transformers import RobertaPreTrainedModel, RobertaModel
+from .configuration_emoaxis import EmoAxisConfig
+
+class EmoAxis(RobertaPreTrainedModel):
+    config_class = EmoAxisConfig
+    def __init__(self, config):
+        super().__init__(config)
+        self.roberta = RobertaModel(config, add_pooling_layer=False)
+        self.mlp = nn.Sequential(
+            nn.Linear(config.hidden_size, 512),
+            nn.LayerNorm(512),
+            nn.GELU(),
+            nn.Dropout(0.25),
+            nn.Linear(512, config.num_classes)
+        )
+        self.post_init()
+    def forward(self, input_ids=None, attention_mask=None, **kwargs):
+        outputs = self.roberta(input_ids=input_ids, attention_mask=attention_mask, output_hidden_states=True)
+        last_hidden_state = outputs.hidden_states[-1]
+        mask = attention_mask.unsqueeze(-1).float()
+        text_emb = (last_hidden_state * mask).sum(dim=1) / mask.sum(dim=1).clamp(min=1e-9)
+        text_emb = F.normalize(text_emb, p=2, dim=1)
+        logits = self.mlp(text_emb)
+        return text_emb, logits

special_tokens_map.json

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+{
+  "bos_token": "<s>",
+  "cls_token": "<s>",
+  "eos_token": "</s>",
+  "mask_token": {
+    "content": "<mask>",
+    "lstrip": true,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": "<pad>",
+  "sep_token": "</s>",
+  "unk_token": "<unk>"
+}

tokenizer_config.json

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+{
+  "add_prefix_space": false,
+  "added_tokens_decoder": {
+    "0": {
+      "content": "<s>",
+      "lstrip": false,
+      "normalized": true,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "1": {
+      "content": "<pad>",
+      "lstrip": false,
+      "normalized": true,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "2": {
+      "content": "</s>",
+      "lstrip": false,
+      "normalized": true,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "3": {
+      "content": "<unk>",
+      "lstrip": false,
+      "normalized": true,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "50264": {
+      "content": "<mask>",
+      "lstrip": true,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "bos_token": "<s>",
+  "clean_up_tokenization_spaces": false,
+  "cls_token": "<s>",
+  "eos_token": "</s>",
+  "errors": "replace",
+  "extra_special_tokens": {},
+  "mask_token": "<mask>",
+  "model_max_length": 512,
+  "pad_token": "<pad>",
+  "sep_token": "</s>",
+  "tokenizer_class": "RobertaTokenizer",
+  "trim_offsets": true,
+  "unk_token": "<unk>"
+}