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SentimentT2_BertBase

Text Classification
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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: bert-base-uncased
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - accuracy
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+ - f1
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+ model-index:
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+ - name: SentimentT2_BertBase
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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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+ # SentimentT2_BertBase
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+
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+ This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.5383
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+ - Accuracy: 0.8532
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+ - F1: 0.8589
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+ - Auc Roc: 0.9323
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+ - Log Loss: 0.5383
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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: 1e-05
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+ - train_batch_size: 16
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+ - eval_batch_size: 20
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+ - seed: 42
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+ - gradient_accumulation_steps: 2
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+ - total_train_batch_size: 32
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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_steps: 500
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+ - num_epochs: 10
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Auc Roc | Log Loss |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:-------:|:--------:|
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+ | 0.6992 | 1.0 | 101 | 0.6441 | 0.6480 | 0.6941 | 0.7125 | 0.6441 |
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+ | 0.5998 | 2.0 | 203 | 0.5229 | 0.7687 | 0.7969 | 0.8658 | 0.5229 |
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+ | 0.4443 | 3.0 | 304 | 0.3993 | 0.8333 | 0.8504 | 0.9189 | 0.3993 |
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+ | 0.3495 | 4.0 | 406 | 0.3888 | 0.8333 | 0.8514 | 0.9282 | 0.3888 |
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+ | 0.3051 | 5.0 | 507 | 0.3459 | 0.8644 | 0.8740 | 0.9328 | 0.3459 |
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+ | 0.2275 | 6.0 | 609 | 0.3825 | 0.8570 | 0.8606 | 0.9327 | 0.3825 |
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+ | 0.1594 | 7.0 | 710 | 0.4236 | 0.8657 | 0.8717 | 0.9341 | 0.4236 |
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+ | 0.108 | 8.0 | 812 | 0.4961 | 0.8520 | 0.8602 | 0.9329 | 0.4961 |
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+ | 0.0747 | 9.0 | 913 | 0.5362 | 0.8570 | 0.8642 | 0.9321 | 0.5362 |
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+ | 0.0643 | 9.95 | 1010 | 0.5383 | 0.8532 | 0.8589 | 0.9323 | 0.5383 |
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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
config.json ADDED
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+ {
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+ "_name_or_path": "bert-base-uncased",
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+ "architectures": [
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+ "BertForSequenceClassification"
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+ ],
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+ "attention_probs_dropout_prob": 0.1,
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+ "classifier_dropout": null,
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+ "gradient_checkpointing": false,
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+ "hidden_act": "gelu",
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+ "hidden_dropout_prob": 0.1,
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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": "4.35.2",
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+ "type_vocab_size": 2,
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+ "use_cache": true,
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+ "vocab_size": 30522
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+ }
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