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End of training

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README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: agpl-3.0
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+ base_model: vinai/phobert-base-v2
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: 7k-PhoContent-200
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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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+ # 7k-PhoContent-200
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+
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+ This model is a fine-tuned version of [vinai/phobert-base-v2](https://huggingface.co/vinai/phobert-base-v2) on the None dataset.
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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: 64
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+ - eval_batch_size: 64
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+ - seed: 42
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 256
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: cosine
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+ - lr_scheduler_warmup_ratio: 0.1
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+ - num_epochs: 20
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+
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+ ### Training results
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+
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.45.1
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+ - Pytorch 2.4.0
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+ - Datasets 3.0.1
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+ - Tokenizers 0.20.0
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+ "RobertaForSequenceClassification"
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+ "layer_norm_eps": 1e-05,
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+ "max_position_embeddings": 258,
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+ "model_type": "roberta",
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+ "num_attention_heads": 12,
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+ "num_hidden_layers": 12,
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+ "pad_token_id": 1,
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+ "position_embedding_type": "absolute",
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+ "problem_type": "single_label_classification",
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+ "tokenizer_class": "PhobertTokenizer",
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.45.1",
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+ "type_vocab_size": 1,
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+ "use_cache": true,
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