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output1

Text Classification
Transformers
Safetensors
deberta-v2
Generated from Trainer
Inference Endpoints
Model card Files Community
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  1. README.md +76 -0
  2. model-00001-of-00002.safetensors +3 -0
  3. model-00002-of-00002.safetensors +3 -0
  4. model.safetensors.index.json +789 -0
README.md ADDED
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+ ---
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+ license: mit
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+ base_model: microsoft/deberta-v2-xxlarge
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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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+ model-index:
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+ - name: output1
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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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+ # output1
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+
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+ This model is a fine-tuned version of [microsoft/deberta-v2-xxlarge](https://huggingface.co/microsoft/deberta-v2-xxlarge) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.7690
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+ - Accuracy: 0.676
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+ - Macro F1: 0.6761
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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: 6e-06
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+ - train_batch_size: 1
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+ - eval_batch_size: 1
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+ - seed: 42
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+ - gradient_accumulation_steps: 64
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+ - total_train_batch_size: 64
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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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+ - 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 | Macro F1 |
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+ |:-------------:|:------:|:----:|:---------------:|:--------:|:--------:|
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+ | 1.5278 | 0.2286 | 100 | 1.1249 | 0.5146 | 0.4600 |
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+ | 0.9452 | 0.4571 | 200 | 0.8437 | 0.645 | 0.6425 |
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+ | 0.8367 | 0.6857 | 300 | 0.8038 | 0.6477 | 0.6531 |
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+ | 0.8092 | 0.9143 | 400 | 0.7801 | 0.6593 | 0.6611 |
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+ | 0.7679 | 1.1429 | 500 | 0.7868 | 0.6717 | 0.6697 |
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+ | 0.7451 | 1.3714 | 600 | 0.7711 | 0.6647 | 0.6645 |
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+ | 0.7467 | 1.6 | 700 | 0.7646 | 0.6659 | 0.6649 |
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+ | 0.7261 | 1.8286 | 800 | 0.7840 | 0.6649 | 0.6632 |
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+ | 0.7305 | 2.0571 | 900 | 0.7755 | 0.6681 | 0.6707 |
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+ | 0.6742 | 2.2857 | 1000 | 0.7719 | 0.6691 | 0.6707 |
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+ | 0.6728 | 2.5143 | 1100 | 0.7640 | 0.6726 | 0.6726 |
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+ | 0.6691 | 2.7429 | 1200 | 0.7759 | 0.6761 | 0.6783 |
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+ | 0.677 | 2.9714 | 1300 | 0.7690 | 0.676 | 0.6761 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.40.0
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+ - Pytorch 2.2.2
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+ - Datasets 2.19.0
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+ - Tokenizers 0.19.1
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