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Duplicate from autoevaluate/multi-class-classification

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Co-authored-by: Lewis Tunstall <[email protected]>

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+ checkpoint-*/
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+ ---
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+ license: apache-2.0
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - emotion
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+ metrics:
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+ - accuracy
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+ duplicated_from: autoevaluate/multi-class-classification
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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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+ # multi-class-classification
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+
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+ This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the emotion dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.2009
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+ - Accuracy: 0.928
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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: 1
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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 |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 0.2643 | 1.0 | 1000 | 0.2009 | 0.928 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.19.2
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+ - Pytorch 1.11.0+cu113
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+ - Datasets 2.2.2
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+ - Tokenizers 0.12.1
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+ {
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+ "_name_or_path": "distilbert-base-uncased",
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+ "activation": "gelu",
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+ "architectures": [
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+ "DistilBertForSequenceClassification"
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+ ],
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+ "attention_dropout": 0.1,
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+ "dim": 768,
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+ "dropout": 0.1,
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+ "hidden_dim": 3072,
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+ "id2label": {
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+ "0": "sadness",
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+ "1": "joy",
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+ "2": "love",
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+ "3": "anger",
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+ "4": "fear",
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+ "5": "surprise"
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+ },
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+ "initializer_range": 0.02,
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+ "label2id": {
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+ "sadness": 0,
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+ "joy": 1,
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+ "love": 2,
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+ "anger": 3,
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+ "fear": 4,
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+ "surprise": 5
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+ },
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+ "max_position_embeddings": 512,
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+ "model_type": "distilbert",
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+ "problem_type": "single_label_classification",
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+ "transformers_version": "4.19.2",
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+ }
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