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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: albert-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: HorAI-medium-17k-albertv2
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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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+ # HorAI-medium-17k-albertv2
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+
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+ This model is a fine-tuned version of [albert-base-v2](https://huggingface.co/albert-base-v2) on an unknown 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: 384
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+ - eval_batch_size: 48
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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: 5.0
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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 4.34.0.dev0
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+ - Pytorch 2.0.1+cu118
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+ - Datasets 2.14.5
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+ - Tokenizers 0.13.3
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+ "_name_or_path": "albert-base-v2",
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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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+ "bos_token_id": 2,
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+ "eos_token_id": 3,
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+ "finetuning_task": "text-classification",
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+ "gap_size": 0,
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+ "hidden_act": "gelu_new",
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+ "hidden_dropout_prob": 0,
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+ "hidden_size": 768,
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+ "id2label": {
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+ },
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+ "initializer_range": 0.02,
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+ },
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+ "layer_norm_eps": 1e-12,
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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_attention_heads": 12,
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+ "num_hidden_groups": 1,
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+ "num_hidden_layers": 12,
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+ "num_memory_blocks": 0,
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+ "pad_token_id": 0,
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+ "position_embedding_type": "absolute",
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+ "problem_type": "single_label_classification",
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.34.0.dev0",
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+ "type_vocab_size": 2,
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+ "vocab_size": 30000
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+ }
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