End of training

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: bert-base-uncased
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: BERT-political_bias-finetune
+  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. -->
+
+# BERT-political_bias-finetune
+
+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: 0.0945
+- Accuracy: 0.9890
+- Precision: 0.9962
+- Recall: 0.9875
+- F1: 0.9918
+
+## 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: 4
+- eval_batch_size: 4
+- seed: 0
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
+|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| 0.2651        | 0.1834 | 500  | 0.5210          | 0.8885   | 0.9981    | 0.8363 | 0.9101 |
+| 0.1807        | 0.3668 | 1000 | 0.1013          | 0.9846   | 0.9913    | 0.9859 | 0.9885 |
+| 0.0872        | 0.5503 | 1500 | 0.0693          | 0.9879   | 0.9860    | 0.9962 | 0.9911 |
+| 0.0775        | 0.7337 | 2000 | 0.1155          | 0.9787   | 0.9961    | 0.9723 | 0.9840 |
+| 0.0751        | 0.9171 | 2500 | 0.0530          | 0.9901   | 0.9945    | 0.9908 | 0.9926 |
+| 0.033         | 1.1005 | 3000 | 0.0505          | 0.9930   | 0.9956    | 0.9940 | 0.9948 |
+| 0.0403        | 1.2839 | 3500 | 0.0447          | 0.9905   | 0.9908    | 0.9951 | 0.9929 |
+| 0.0395        | 1.4674 | 4000 | 0.0857          | 0.9868   | 0.9967    | 0.9837 | 0.9901 |
+| 0.0077        | 1.6508 | 4500 | 0.0708          | 0.9912   | 0.9903    | 0.9967 | 0.9935 |
+| 0.0342        | 1.8342 | 5000 | 0.0945          | 0.9890   | 0.9962    | 0.9875 | 0.9918 |
+
+
+### Framework versions
+
+- Transformers 4.44.2
+- Pytorch 2.4.1+cu121
+- Datasets 3.0.1
+- Tokenizers 0.19.1

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": "4.44.2",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30522
+}

model.safetensors

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+size 437958648

runs/Sep26_17-59-53_4907bdbe5530/events.out.tfevents.1727373601.4907bdbe5530.874.0

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training_args.bin

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