End of training

README.md

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+---
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: training_outputs
+  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_outputs
+
+This model was trained from scratch on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0394
+- Accuracy: 0.993
+- Precision: 0.9913
+- Recall: 0.9884
+- F1: 0.9899
+- Roc Auc: 0.9988
+
+## 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: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 1
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Accuracy | Precision | Recall | F1     | Roc Auc |
+|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:-------:|
+| 0.045         | 0.1105 | 1000 | 0.0609          | 0.987    | 0.9798    | 0.9827 | 0.9812 | 0.9990  |
+| 0.0539        | 0.2210 | 2000 | 0.0471          | 0.988    | 0.9883    | 0.9769 | 0.9826 | 0.9985  |
+| 0.0467        | 0.3316 | 3000 | 0.0546          | 0.989    | 0.9855    | 0.9827 | 0.9841 | 0.9989  |
+| 0.0439        | 0.4421 | 4000 | 0.0416          | 0.99     | 0.9884    | 0.9827 | 0.9855 | 0.9990  |
+| 0.0419        | 0.5526 | 5000 | 0.0470          | 0.99     | 0.9855    | 0.9855 | 0.9855 | 0.9991  |
+| 0.0395        | 0.6631 | 6000 | 0.0396          | 0.992    | 0.9884    | 0.9884 | 0.9884 | 0.9970  |
+| 0.0329        | 0.7737 | 7000 | 0.0427          | 0.993    | 0.9885    | 0.9913 | 0.9899 | 0.9986  |
+| 0.0373        | 0.8842 | 8000 | 0.0408          | 0.992    | 0.9884    | 0.9884 | 0.9884 | 0.9988  |
+| 0.031         | 0.9947 | 9000 | 0.0394          | 0.993    | 0.9913    | 0.9884 | 0.9899 | 0.9988  |
+
+
+### Framework versions
+
+- Transformers 4.41.2
+- Pytorch 2.3.0+cu121
+- Datasets 2.20.0
+- Tokenizers 0.19.1

config.json

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+{
+  "_name_or_path": "/content/drive/MyDrive/training_outputs/checkpoint-17000",
+  "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": "4.41.2",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30522
+}

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