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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: microsoft/deberta-v3-small
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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: deberta-v3-small-finetuned-mnli
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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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+ # deberta-v3-small-finetuned-mnli
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+
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+ This model is a fine-tuned version of [microsoft/deberta-v3-small](https://huggingface.co/microsoft/deberta-v3-small) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.6370
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+ - Accuracy: 0.8776
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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: 5
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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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+ | 0.3771 | 1.0 | 24544 | 0.3509 | 0.8689 |
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+ | 0.2918 | 2.0 | 49088 | 0.3752 | 0.8720 |
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+ | 0.2278 | 3.0 | 73632 | 0.4424 | 0.8756 |
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+ | 0.1727 | 4.0 | 98176 | 0.5483 | 0.8768 |
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+ | 0.1413 | 5.0 | 122720 | 0.6370 | 0.8776 |
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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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+ "_name_or_path": "microsoft/deberta-v3-small",
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+ "architectures": [
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+ "DebertaV2ForSequenceClassification"
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+ ],
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+ "attention_probs_dropout_prob": 0.1,
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+ "hidden_dropout_prob": 0.1,
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+ "layer_norm_eps": 1e-07,
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+ "max_position_embeddings": 512,
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+ "max_relative_positions": -1,
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+ "model_type": "deberta-v2",
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+ "norm_rel_ebd": "layer_norm",
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+ "num_attention_heads": 12,
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+ "num_hidden_layers": 6,
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+ "pooler_hidden_act": "gelu",
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