Training completed

README.md

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+---
+base_model: nghuyong/ernie-1.0
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+- precision
+- recall
+model-index:
+- name: Ernie-PoliticalBias-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. -->
+
+# Ernie-PoliticalBias-Finetune
+
+This model is a fine-tuned version of [nghuyong/ernie-1.0](https://huggingface.co/nghuyong/ernie-1.0) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4782
+- Accuracy: 0.8021
+- F1: 0.7908
+- Precision: 0.8155
+- Recall: 0.7776
+
+## 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: 500
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     | Precision | Recall |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
+| 0.587         | 1.0   | 3845  | 0.5531          | 0.7607   | 0.7532 | 0.7679    | 0.7454 |
+| 0.7662        | 2.0   | 7690  | 0.5028          | 0.7948   | 0.7839 | 0.8301    | 0.7626 |
+| 0.4928        | 3.0   | 11535 | 0.4782          | 0.8021   | 0.7908 | 0.8155    | 0.7776 |
+| 0.414         | 4.0   | 15380 | 0.5139          | 0.8179   | 0.8043 | 0.8335    | 0.7878 |
+| 0.2473        | 5.0   | 19225 | 0.5511          | 0.8218   | 0.8103 | 0.8193    | 0.8033 |
+
+
+### Framework versions
+
+- Transformers 4.40.2
+- Pytorch 2.1.2
+- Datasets 2.19.1
+- Tokenizers 0.19.1

config.json

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+{
+  "_name_or_path": "nghuyong/ernie-1.0",
+  "architectures": [
+    "ErnieForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "hidden_act": "relu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "LeftWing",
+    "1": "Neutral",
+    "2": "RightWing"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "LABEL_0": 0,
+    "LABEL_1": 1,
+    "LABEL_2": 2
+  },
+  "layer_norm_eps": 1e-05,
+  "max_position_embeddings": 513,
+  "model_type": "ernie",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "problem_type": "single_label_classification",
+  "task_type_vocab_size": 3,
+  "torch_dtype": "float32",
+  "transformers_version": "4.40.2",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "use_task_id": false,
+  "vocab_size": 18000
+}

model.safetensors

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+size 399497348

special_tokens_map.json

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

tokenizer_config.json

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+{
+  "added_tokens_decoder": {
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+      "lstrip": false,
+      "normalized": false,
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+  "clean_up_tokenization_spaces": true,
+  "cls_token": "[CLS]",
+  "do_basic_tokenize": true,
+  "do_lower_case": true,
+  "full_tokenizer_file": null,
+  "mask_token": "[MASK]",
+  "model_max_length": 1000000000000000019884624838656,
+  "never_split": null,
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "BertTokenizer",
+  "unk_token": "[UNK]"
+}

training_args.bin

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