End of training

README.md

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+---
+license: mit
+base_model: MoritzLaurer/deberta-v3-large-zeroshot-v2.0
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: fine-tuned-MoritzLaurer-deberta-v3-large-zeroshot-v2.0-arceasy
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# fine-tuned-MoritzLaurer-deberta-v3-large-zeroshot-v2.0-arceasy
+
+This model is a fine-tuned version of [MoritzLaurer/deberta-v3-large-zeroshot-v2.0](https://huggingface.co/MoritzLaurer/deberta-v3-large-zeroshot-v2.0) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.8204
+- Accuracy: 0.8175
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 1.5e-05
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 6
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| No log        | 1.0   | 141  | 0.4636          | 0.8333   |
+| No log        | 2.0   | 282  | 0.5887          | 0.8175   |
+| No log        | 3.0   | 423  | 0.5583          | 0.8316   |
+| 0.3291        | 4.0   | 564  | 0.7024          | 0.8246   |
+| 0.3291        | 5.0   | 705  | 0.7975          | 0.8246   |
+| 0.3291        | 6.0   | 846  | 0.8204          | 0.8175   |
+
+
+### Framework versions
+
+- Transformers 4.41.2
+- Pytorch 2.3.0+cu121
+- Datasets 2.20.0
+- Tokenizers 0.19.1

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