End of training

README.md

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+---
+license: apache-2.0
+base_model: bert-base-uncased
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: training-5
+  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. -->
+
+# training-5
+
+This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0341
+- Accuracy: 0.9952
+- Precision: 0.9982
+- Recall: 0.9841
+- F1: 0.9911
+
+## 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: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| No log        | 0.25  | 151  | 0.0468          | 0.9923   | 1.0       | 0.9717 | 0.9856 |
+| No log        | 0.5   | 302  | 0.0497          | 0.9908   | 0.9840    | 0.9823 | 0.9832 |
+| No log        | 0.75  | 453  | 0.0571          | 0.9918   | 1.0       | 0.9699 | 0.9847 |
+| No log        | 1.0   | 604  | 0.0319          | 0.9961   | 1.0       | 0.9858 | 0.9929 |
+| 0.0471        | 1.25  | 755  | 0.0353          | 0.9952   | 0.9982    | 0.9841 | 0.9911 |
+| 0.0471        | 1.5   | 906  | 0.0346          | 0.9942   | 0.9929    | 0.9858 | 0.9893 |
+| 0.0471        | 1.75  | 1057 | 0.0678          | 0.9899   | 0.9772    | 0.9858 | 0.9815 |
+| 0.0471        | 2.0   | 1208 | 0.0380          | 0.9952   | 1.0       | 0.9823 | 0.9911 |
+| 0.0156        | 2.25  | 1359 | 0.0362          | 0.9952   | 1.0       | 0.9823 | 0.9911 |
+| 0.0156        | 2.5   | 1510 | 0.0388          | 0.9942   | 0.9946    | 0.9841 | 0.9893 |
+| 0.0156        | 2.75  | 1661 | 0.0418          | 0.9952   | 1.0       | 0.9823 | 0.9911 |
+| 0.0156        | 3.0   | 1812 | 0.0333          | 0.9952   | 0.9982    | 0.9841 | 0.9911 |
+| 0.0121        | 3.24  | 1963 | 0.0326          | 0.9952   | 0.9982    | 0.9841 | 0.9911 |
+| 0.0121        | 3.49  | 2114 | 0.0309          | 0.9957   | 0.9982    | 0.9858 | 0.9920 |
+| 0.0121        | 3.74  | 2265 | 0.0311          | 0.9952   | 0.9982    | 0.9841 | 0.9911 |
+| 0.0121        | 3.99  | 2416 | 0.0344          | 0.9952   | 0.9982    | 0.9841 | 0.9911 |
+| 0.0084        | 4.24  | 2567 | 0.0334          | 0.9952   | 0.9982    | 0.9841 | 0.9911 |
+| 0.0084        | 4.49  | 2718 | 0.0327          | 0.9952   | 0.9982    | 0.9841 | 0.9911 |
+| 0.0084        | 4.74  | 2869 | 0.0336          | 0.9952   | 0.9982    | 0.9841 | 0.9911 |
+| 0.0084        | 4.99  | 3020 | 0.0341          | 0.9952   | 0.9982    | 0.9841 | 0.9911 |
+
+
+### Framework versions
+
+- Transformers 4.33.1
+- Pytorch 2.2.0.dev20230913+cu121
+- Tokenizers 0.13.3

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": "4.33.1",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30522
+}

pytorch_model.bin

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training_args.bin

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