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End of training

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README.md ADDED
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+ ---
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+ base_model: jjzha/jobbert-base-cased
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: jobbert-base-cased-compdecs
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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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+ # jobbert-base-cased-compdecs
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+
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+ This model is a fine-tuned version of [jjzha/jobbert-base-cased](https://huggingface.co/jjzha/jobbert-base-cased) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.4622
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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: 16
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+ - eval_batch_size: 16
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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: 10
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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 4.32.0
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+ - Pytorch 2.0.1+cu118
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+ - Datasets 2.14.4
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+ - Tokenizers 0.13.3
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+ "_name_or_path": "jjzha/jobbert-base-cased",
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+ "BertForSequenceClassification"
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+ "gradient_checkpointing": false,
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+ "hidden_act": "gelu",
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+ "hidden_size": 768,
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+ "initializer_range": 0.02,
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+ "intermediate_size": 3072,
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+ "layer_norm_eps": 1e-12,
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+ "max_position_embeddings": 512,
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+ "model_type": "bert",
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+ "num_attention_heads": 12,
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+ "num_hidden_layers": 12,
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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": "4.32.0",
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+ "type_vocab_size": 2,
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+ "use_cache": true,
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+ "vocab_size": 28996
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+ }
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tokenizer_config.json ADDED
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