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End of training

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README.md ADDED
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+ ---
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+ license: gpl-3.0
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+ base_model: ckiplab/albert-base-chinese
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - f1
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+ - accuracy
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+ model-index:
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+ - name: bert-base-chinese
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # bert-base-chinese
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+
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+ This model is a fine-tuned version of [ckiplab/albert-base-chinese](https://huggingface.co/ckiplab/albert-base-chinese) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.6943
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+ - F1: 0.5455
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+ - Roc Auc: 0.5500
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+ - Accuracy: 0.0
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 2e-05
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+ - train_batch_size: 128
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+ - eval_batch_size: 128
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+ - seed: 42
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - num_epochs: 5
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
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+ | No log | 1.0 | 1 | 0.6943 | 0.5455 | 0.5500 | 0.0 |
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+ | No log | 2.0 | 2 | 0.6945 | 0.5455 | 0.5500 | 0.0 |
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+ | No log | 3.0 | 3 | 0.6947 | 0.5455 | 0.5500 | 0.0 |
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+ | No log | 4.0 | 4 | 0.6949 | 0.5455 | 0.5500 | 0.0 |
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+ | No log | 5.0 | 5 | 0.6949 | 0.5455 | 0.5500 | 0.0 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.35.2
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+ - Pytorch 2.1.0+cu121
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+ - Datasets 2.16.1
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+ - Tokenizers 0.15.0
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+ {
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+ "_name_or_path": "ckiplab/albert-base-chinese",
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+ "architectures": [
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+ "AlbertForSequenceClassification"
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+ ],
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+ "attention_probs_dropout_prob": 0,
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+ "gap_size": 0,
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+ "hidden_act": "relu",
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+ "hidden_dropout_prob": 0,
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+ "hidden_size": 768,
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+ "id2label": {
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+ "0": "anger",
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+ "1": "anticipation",
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+ "2": "disgust",
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+ "3": "fear",
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+ "4": "joy",
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+ "5": "love",
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+ "6": "optimism",
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+ "7": "pessimism",
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+ "8": "sadness",
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+ "9": "surprise",
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+ "10": "trust"
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+ },
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+ "initializer_range": 0.02,
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+ "layer_norm_eps": 1e-12,
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+ "layers_to_keep": [],
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+ "max_position_embeddings": 512,
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+ "model_type": "albert",
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+ "net_structure_type": 0,
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+ "num_hidden_layers": 12,
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+ "position_embedding_type": "absolute",
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+ "problem_type": "multi_label_classification",
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+ "tokenizer_class": "BertTokenizerFast",
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.35.2",
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+ "type_vocab_size": 2,
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+ }
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