Training in progress, epoch 1

.gitignore

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+checkpoint-*/

added_tokens.json

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+{
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+}

config.json

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+{
+  "_name_or_path": "microsoft/deberta-v3-base",
+  "architectures": [
+    "DebertaV2ForTokenClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "hidden_act": "gelu",
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+  "hidden_size": 768,
+  "id2label": {
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+    "1": "B-Appeal_to_fear-prejudice",
+    "2": "I-Appeal_to_fear-prejudice",
+    "3": "B-Whataboutism",
+    "4": "I-Whataboutism",
+    "5": "B-Doubt",
+    "6": "I-Doubt",
+    "7": "B-Name_Calling,Labeling",
+    "8": "I-Name_Calling,Labeling"
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+  "intermediate_size": 3072,
+  "label2id": {
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+    "B-Doubt": 5,
+    "B-Name_Calling,Labeling": 7,
+    "B-Whataboutism": 3,
+    "I-Appeal_to_fear-prejudice": 2,
+    "I-Doubt": 6,
+    "I-Name_Calling,Labeling": 8,
+    "I-Whataboutism": 4,
+    "O": 0
+  },
+  "layer_norm_eps": 1e-07,
+  "max_position_embeddings": 512,
+  "max_relative_positions": -1,
+  "model_type": "deberta-v2",
+  "norm_rel_ebd": "layer_norm",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 0,
+  "pooler_dropout": 0,
+  "pooler_hidden_act": "gelu",
+  "pooler_hidden_size": 768,
+  "pos_att_type": [
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+    "c2p"
+  ],
+  "position_biased_input": false,
+  "position_buckets": 256,
+  "relative_attention": true,
+  "share_att_key": true,
+  "torch_dtype": "float32",
+  "transformers_version": "4.30.0",
+  "type_vocab_size": 0,
+  "vocab_size": 128100
+}

pytorch_model.bin

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runs/Apr26_11-14-07_bb8-lix.polytechnique.fr/events.out.tfevents.1714122854.bb8-lix.polytechnique.fr.166787.0

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special_tokens_map.json

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+{
+  "bos_token": "[CLS]",
+  "cls_token": "[CLS]",
+  "eos_token": "[SEP]",
+  "mask_token": "[MASK]",
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "unk_token": "[UNK]"
+}

spm.model

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tokenizer_config.json

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+{
+  "bos_token": "[CLS]",
+  "clean_up_tokenization_spaces": true,
+  "cls_token": "[CLS]",
+  "do_lower_case": false,
+  "eos_token": "[SEP]",
+  "mask_token": "[MASK]",
+  "model_max_length": 1000000000000000019884624838656,
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "sp_model_kwargs": {},
+  "split_by_punct": false,
+  "tokenizer_class": "DebertaV2Tokenizer",
+  "unk_token": "[UNK]",
+  "vocab_type": "spm"
+}

training_args.bin

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