Training complete

README.md

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+---
+license: mit
+base_model: microsoft/deberta-v3-base
+tags:
+- generated_from_trainer
+model-index:
+- name: ner-wand-test
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# ner-wand-test
+
+This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the None dataset.
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 2e-05
+- train_batch_size: 8
+- eval_batch_size: 16
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 16
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 30
+- mixed_precision_training: Native AMP
+
+### Training results
+
+
+
+### Framework versions
+
+- Transformers 4.37.0
+- Pytorch 2.1.2
+- Datasets 2.1.0
+- Tokenizers 0.15.1

added_tokens.json

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+}

config.json

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+{
+  "_name_or_path": "microsoft/deberta-v3-base",
+  "architectures": [
+    "DebertaV2ForTokenClassification"
+  ],
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+  "hidden_act": "gelu",
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+    "12": "B-BIOLOGICAL_STRUCTURE",
+    "13": "B-CLINICAL_EVENT",
+    "14": "I-CLINICAL_EVENT",
+    "15": "B-COLOR",
+    "16": "I-COLOR",
+    "17": "I-COREFERENCE",
+    "18": "B-COREFERENCE",
+    "19": "B-DATE",
+    "20": "I-DATE",
+    "21": "I-DETAILED_DESCRIPTION",
+    "22": "B-DETAILED_DESCRIPTION",
+    "23": "I-DIAGNOSTIC_PROCEDURE",
+    "24": "B-DIAGNOSTIC_PROCEDURE",
+    "25": "I-DISEASE_DISORDER",
+    "26": "B-DISEASE_DISORDER",
+    "27": "B-DISTANCE",
+    "28": "I-DISTANCE",
+    "29": "B-DOSAGE",
+    "30": "I-DOSAGE",
+    "31": "I-DURATION",
+    "32": "B-DURATION",
+    "33": "I-FAMILY_HISTORY",
+    "34": "B-FAMILY_HISTORY",
+    "35": "B-FREQUENCY",
+    "36": "I-FREQUENCY",
+    "37": "I-HEIGHT",
+    "38": "B-HEIGHT",
+    "39": "B-HISTORY",
+    "40": "I-HISTORY",
+    "41": "I-LAB_VALUE",
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+    "I-DURATION": 31,
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+    "I-FREQUENCY": 36,
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+    "I-OTHER_ENTITY": 52,
+    "I-OTHER_EVENT": 54,
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+  "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,
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+  "pooler_dropout": 0,
+  "pooler_hidden_act": "gelu",
+  "pooler_hidden_size": 768,
+  "pos_att_type": [
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+  "position_biased_input": false,
+  "position_buckets": 256,
+  "relative_attention": true,
+  "share_att_key": true,
+  "torch_dtype": "float32",
+  "transformers_version": "4.37.0",
+  "type_vocab_size": 0,
+  "vocab_size": 128100
+}

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runs/Feb12_07-26-02_db5e1b3cab0a/events.out.tfevents.1707722770.db5e1b3cab0a.35.0

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special_tokens_map.json

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tokenizer_config.json

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+}

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