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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: xlnet/xlnet-base-cased
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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: emotion_xlnet
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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: test
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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: 0.9145
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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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+ # emotion_xlnet
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+
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+ This model is a fine-tuned version of [xlnet/xlnet-base-cased](https://huggingface.co/xlnet/xlnet-base-cased) on the emotion dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1996
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+ - Accuracy: 0.9145
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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: 64
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+ - eval_batch_size: 64
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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: 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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+ | No log | 1.0 | 250 | 0.3686 | 0.8695 |
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+ | 0.5792 | 2.0 | 500 | 0.2257 | 0.908 |
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+ | 0.5792 | 3.0 | 750 | 0.1996 | 0.9145 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.37.2
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+ - Pytorch 2.1.0+cu121
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+ - Datasets 2.17.1
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+ - Tokenizers 0.15.2
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+ "eos_token_id": 2,
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+ "ff_activation": "gelu",
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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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+ "anger": 3,
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+ "fear": 4,
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+ "joy": 1,
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+ "love": 2,
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+ "sadness": 0,
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+ "surprise": 5
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+ },
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+ }
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+ "untie_r": true,
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+ "use_mems_eval": true,
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+ "vocab_size": 32000
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+ }
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