End of training

README.md

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+---
+library_name: transformers
+license: mit
+base_model: microsoft/deberta-v3-base
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: mdeberta-domain_EN_fold3
+  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. -->
+
+# mdeberta-domain_EN_fold3
+
+This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4288
+- Accuracy: 0.8414
+- Precision: 0.7835
+- Recall: 0.7813
+- F1: 0.7618
+
+## 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: 2e-05
+- train_batch_size: 32
+- eval_batch_size: 32
+- seed: 42
+- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| 1.0342        | 1.0   | 19   | 0.8300          | 0.5931   | 0.8644    | 0.3333 | 0.2482 |
+| 0.7812        | 2.0   | 38   | 0.6683          | 0.6414   | 0.8744    | 0.4111 | 0.3821 |
+| 0.6431        | 3.0   | 57   | 0.6047          | 0.7793   | 0.8260    | 0.6406 | 0.5553 |
+| 0.6002        | 4.0   | 76   | 0.5521          | 0.7931   | 0.8316    | 0.6636 | 0.6016 |
+| 0.4757        | 5.0   | 95   | 0.4576          | 0.7862   | 0.6713    | 0.6974 | 0.6574 |
+| 0.4112        | 6.0   | 114  | 0.5542          | 0.7517   | 0.6641    | 0.7157 | 0.6721 |
+| 0.34          | 7.0   | 133  | 0.4608          | 0.8069   | 0.7236    | 0.7246 | 0.7004 |
+| 0.2907        | 8.0   | 152  | 0.4542          | 0.7931   | 0.7067    | 0.7470 | 0.7149 |
+| 0.2521        | 9.0   | 171  | 0.4539          | 0.8138   | 0.7410    | 0.7811 | 0.7514 |
+| 0.2023        | 10.0  | 190  | 0.4288          | 0.8414   | 0.7835    | 0.7813 | 0.7618 |
+
+
+### Framework versions
+
+- Transformers 4.46.0
+- Pytorch 2.3.1
+- Datasets 2.21.0
+- Tokenizers 0.20.1

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