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End of training

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README.md ADDED
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+ ---
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+ base_model: gokuls/model_v1_complete_training_wt_init_48_mini
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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: hbertv1-mini-wt-48-emotion
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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: 0.908
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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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+ # hbertv1-mini-wt-48-emotion
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+
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+ This model is a fine-tuned version of [gokuls/model_v1_complete_training_wt_init_48_mini](https://huggingface.co/gokuls/model_v1_complete_training_wt_init_48_mini) on the emotion dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.2561
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+ - Accuracy: 0.908
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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: 5e-05
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+ - train_batch_size: 64
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+ - eval_batch_size: 64
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+ - seed: 33
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+ - distributed_type: multi-GPU
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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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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 1.0852 | 1.0 | 250 | 0.5567 | 0.8195 |
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+ | 0.4522 | 2.0 | 500 | 0.3409 | 0.8775 |
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+ | 0.3152 | 3.0 | 750 | 0.3007 | 0.8885 |
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+ | 0.2646 | 4.0 | 1000 | 0.2999 | 0.9045 |
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+ | 0.23 | 5.0 | 1250 | 0.2842 | 0.8945 |
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+ | 0.205 | 6.0 | 1500 | 0.2658 | 0.9035 |
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+ | 0.1871 | 7.0 | 1750 | 0.2674 | 0.902 |
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+ | 0.1623 | 8.0 | 2000 | 0.2561 | 0.908 |
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+ | 0.1488 | 9.0 | 2250 | 0.2529 | 0.9075 |
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+ | 0.1379 | 10.0 | 2500 | 0.2523 | 0.908 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.31.0
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+ - Pytorch 1.14.0a0+410ce96
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+ - Datasets 2.13.1
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+ - Tokenizers 0.13.3
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