End of training

README.md

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+---
+library_name: transformers
+license: mit
+base_model: microsoft/mdeberta-v3-base
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: mdeberta-domain_fold4
+  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_fold4
+
+This model is a fine-tuned version of [microsoft/mdeberta-v3-base](https://huggingface.co/microsoft/mdeberta-v3-base) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3705
+- Accuracy: 0.8552
+- Precision: 0.8128
+- Recall: 0.8276
+- F1: 0.8194
+
+## 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     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| 1.0349        | 1.0   | 19   | 0.9208          | 0.5931   | 0.8644    | 0.3333 | 0.2482 |
+| 0.88          | 2.0   | 38   | 0.7011          | 0.5931   | 0.8644    | 0.3333 | 0.2482 |
+| 0.68          | 3.0   | 57   | 0.6370          | 0.5931   | 0.8644    | 0.3333 | 0.2482 |
+| 0.6179        | 4.0   | 76   | 0.5360          | 0.8      | 0.6860    | 0.6971 | 0.6459 |
+| 0.4709        | 5.0   | 95   | 0.3949          | 0.8483   | 0.7967    | 0.7860 | 0.7852 |
+| 0.3643        | 6.0   | 114  | 0.3526          | 0.8690   | 0.8279    | 0.8209 | 0.8236 |
+| 0.2901        | 7.0   | 133  | 0.3713          | 0.8690   | 0.8269    | 0.8277 | 0.8242 |
+| 0.2414        | 8.0   | 152  | 0.3506          | 0.8759   | 0.8394    | 0.8392 | 0.8374 |
+| 0.1941        | 9.0   | 171  | 0.3766          | 0.8621   | 0.8206    | 0.8391 | 0.8290 |
+| 0.1977        | 10.0  | 190  | 0.3705          | 0.8552   | 0.8128    | 0.8276 | 0.8194 |
+
+
+### Framework versions
+
+- Transformers 4.46.0
+- Pytorch 2.3.1
+- Datasets 2.21.0
+- Tokenizers 0.20.1

model.safetensors

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