add model

.gitignore

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+checkpoint-*/

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- d_bpedia14
+metrics:
+- accuracy
+model-index:
+- name: bert-base-uncased-dbpedia_14
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: d_bpedia14
+      type: d_bpedia14
+      args: dbpedia_14
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.9902857142857143
+---
+
+<!-- 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. -->
+
+# bert-base-uncased-dbpedia_14
+
+This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the d_bpedia14 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0547
+- Accuracy: 0.9903
+
+## 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: 5e-05
+- train_batch_size: 8
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 34650
+- training_steps: 346500
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|
+| 1.7757        | 0.03  | 2000  | 0.2732          | 0.9880   |
+| 0.1002        | 0.06  | 4000  | 0.0620          | 0.9891   |
+| 0.0547        | 0.09  | 6000  | 0.0723          | 0.9879   |
+| 0.0558        | 0.12  | 8000  | 0.0678          | 0.9875   |
+| 0.0534        | 0.14  | 10000 | 0.0554          | 0.9896   |
+| 0.0632        | 0.17  | 12000 | 0.0670          | 0.9888   |
+| 0.0612        | 0.2   | 14000 | 0.0733          | 0.9873   |
+| 0.0667        | 0.23  | 16000 | 0.0623          | 0.9896   |
+| 0.0636        | 0.26  | 18000 | 0.0836          | 0.9868   |
+| 0.0705        | 0.29  | 20000 | 0.0776          | 0.9855   |
+| 0.0726        | 0.32  | 22000 | 0.0805          | 0.9861   |
+| 0.0778        | 0.35  | 24000 | 0.0713          | 0.9870   |
+| 0.0713        | 0.38  | 26000 | 0.1277          | 0.9805   |
+| 0.0965        | 0.4   | 28000 | 0.0810          | 0.9855   |
+| 0.0881        | 0.43  | 30000 | 0.0910          | 0.985    |
+
+
+### Framework versions
+
+- Transformers 4.10.2
+- Pytorch 1.7.1
+- Datasets 1.6.1
+- Tokenizers 0.10.3

config.json

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+{
+  "_name_or_path": "bert-base-uncased",
+  "architectures": [
+    "BertForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "LABEL_0",
+    "1": "LABEL_1",
+    "2": "LABEL_2",
+    "3": "LABEL_3",
+    "4": "LABEL_4",
+    "5": "LABEL_5",
+    "6": "LABEL_6",
+    "7": "LABEL_7",
+    "8": "LABEL_8",
+    "9": "LABEL_9",
+    "10": "LABEL_10",
+    "11": "LABEL_11",
+    "12": "LABEL_12",
+    "13": "LABEL_13"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "LABEL_0": 0,
+    "LABEL_1": 1,
+    "LABEL_10": 10,
+    "LABEL_11": 11,
+    "LABEL_12": 12,
+    "LABEL_13": 13,
+    "LABEL_2": 2,
+    "LABEL_3": 3,
+    "LABEL_4": 4,
+    "LABEL_5": 5,
+    "LABEL_6": 6,
+    "LABEL_7": 7,
+    "LABEL_8": 8,
+    "LABEL_9": 9
+  },
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "problem_type": "single_label_classification",
+  "torch_dtype": "float32",
+  "transformers_version": "4.10.2",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30522
+}

pytorch_model.bin

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special_tokens_map.json

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

tokenizer_config.json

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+{"do_lower_case": true, "unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]", "tokenize_chinese_chars": true, "strip_accents": null, "model_max_length": 512, "special_tokens_map_file": null, "name_or_path": "bert-base-uncased", "tokenizer_class": "BertTokenizer"}

training_args.bin

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