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End of training

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README.md ADDED
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+ ---
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+ license: mit
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+ base_model: FacebookAI/roberta-base
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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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+ model-index:
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+ - name: my_model_nlp_workshop_2
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+ results:
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+ - task:
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+ name: Text Classification
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+ type: text-classification
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+ dataset:
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+ name: emotion
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+ type: emotion
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+ config: split
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+ split: validation
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+ args: split
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+ metrics:
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.942
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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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+ # my_model_nlp_workshop_2
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+
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+ This model is a fine-tuned version of [FacebookAI/roberta-base](https://huggingface.co/FacebookAI/roberta-base) on the emotion dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1369
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+ - Accuracy: 0.942
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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: 224
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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: 3
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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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+ | 0.2639 | 1.0 | 1000 | 0.2136 | 0.9305 |
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+ | 0.1664 | 2.0 | 2000 | 0.1485 | 0.9385 |
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+ | 0.105 | 3.0 | 3000 | 0.1369 | 0.942 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.38.2
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+ - Pytorch 2.1.0+cu121
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+ - Datasets 2.18.0
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+ - Tokenizers 0.15.2
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+ "layer_norm_eps": 1e-05,
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+ "max_position_embeddings": 514,
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+ "model_type": "roberta",
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