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_fold1
+  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_fold1
+
+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: 0.5362
+- Accuracy: 0.8288
+- Precision: 0.7887
+- Recall: 0.7656
+- F1: 0.7752
+
+## 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     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| 1.0312        | 1.0   | 19   | 0.8773          | 0.5890   | 0.8630    | 0.3333 | 0.2471 |
+| 0.7596        | 2.0   | 38   | 0.7653          | 0.5890   | 0.8630    | 0.3333 | 0.2471 |
+| 0.7097        | 3.0   | 57   | 0.7352          | 0.5890   | 0.8630    | 0.3333 | 0.2471 |
+| 0.6673        | 4.0   | 76   | 0.7382          | 0.7466   | 0.6626    | 0.5889 | 0.5519 |
+| 0.6028        | 5.0   | 95   | 0.7362          | 0.7740   | 0.6837    | 0.6406 | 0.5884 |
+| 0.4939        | 6.0   | 114  | 0.6345          | 0.7466   | 0.6145    | 0.6034 | 0.5967 |
+| 0.3969        | 7.0   | 133  | 0.5446          | 0.8014   | 0.7220    | 0.7140 | 0.6938 |
+| 0.3291        | 8.0   | 152  | 0.5437          | 0.8082   | 0.7452    | 0.7468 | 0.7410 |
+| 0.2975        | 9.0   | 171  | 0.5534          | 0.7945   | 0.7437    | 0.7101 | 0.7235 |
+| 0.2573        | 10.0  | 190  | 0.5362          | 0.8288   | 0.7887    | 0.7656 | 0.7752 |
+
+
+### Framework versions
+
+- Transformers 4.46.0
+- Pytorch 2.3.1
+- Datasets 2.21.0
+- Tokenizers 0.20.1

runs/Oct28_16-16-20_icuff-Z790-UD/events.out.tfevents.1730142981.icuff-Z790-UD.1133969.0

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