add model

.gitignore

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+checkpoint-*/

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- yelp_polarity
+metrics:
+- accuracy
+model-index:
+- name: bert-base-uncased-yelp_polarity
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: yelp_polarity
+      type: yelp_polarity
+      args: plain_text
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.9516052631578947
+---
+
+<!-- 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-yelp_polarity
+
+This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the yelp_polarity dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3222
+- Accuracy: 0.9516
+
+## 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: 1
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 277200
+- training_steps: 2772000
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|
+| 0.8067        | 0.0   | 2000  | 0.8241          | 0.4975   |
+| 0.5482        | 0.01  | 4000  | 0.3507          | 0.8591   |
+| 0.3427        | 0.01  | 6000  | 0.3750          | 0.9139   |
+| 0.4133        | 0.01  | 8000  | 0.5520          | 0.9016   |
+| 0.4301        | 0.02  | 10000 | 0.3803          | 0.9304   |
+| 0.3716        | 0.02  | 12000 | 0.4168          | 0.9337   |
+| 0.4076        | 0.03  | 14000 | 0.5042          | 0.9170   |
+| 0.3674        | 0.03  | 16000 | 0.4806          | 0.9268   |
+| 0.3813        | 0.03  | 18000 | 0.4227          | 0.9261   |
+| 0.3723        | 0.04  | 20000 | 0.3360          | 0.9418   |
+| 0.3876        | 0.04  | 22000 | 0.3255          | 0.9407   |
+| 0.3351        | 0.04  | 24000 | 0.3283          | 0.9404   |
+| 0.34          | 0.05  | 26000 | 0.3489          | 0.9430   |
+| 0.3006        | 0.05  | 28000 | 0.3302          | 0.9464   |
+| 0.349         | 0.05  | 30000 | 0.3853          | 0.9375   |
+| 0.3696        | 0.06  | 32000 | 0.2992          | 0.9454   |
+| 0.3301        | 0.06  | 34000 | 0.3484          | 0.9464   |
+| 0.3151        | 0.06  | 36000 | 0.3529          | 0.9455   |
+| 0.3682        | 0.07  | 38000 | 0.3052          | 0.9420   |
+| 0.3184        | 0.07  | 40000 | 0.3323          | 0.9466   |
+| 0.3207        | 0.08  | 42000 | 0.3133          | 0.9532   |
+| 0.3346        | 0.08  | 44000 | 0.3826          | 0.9414   |
+| 0.3008        | 0.08  | 46000 | 0.3059          | 0.9484   |
+| 0.3306        | 0.09  | 48000 | 0.3089          | 0.9475   |
+| 0.342         | 0.09  | 50000 | 0.3611          | 0.9486   |
+| 0.3424        | 0.09  | 52000 | 0.3227          | 0.9445   |
+| 0.3044        | 0.1   | 54000 | 0.3130          | 0.9489   |
+| 0.3278        | 0.1   | 56000 | 0.3827          | 0.9368   |
+| 0.288         | 0.1   | 58000 | 0.3080          | 0.9504   |
+| 0.3342        | 0.11  | 60000 | 0.3252          | 0.9471   |
+| 0.3737        | 0.11  | 62000 | 0.4250          | 0.9343   |
+
+
+### 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,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "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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