End of training

README.md

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+---
+license: mit
+base_model: microsoft/deberta-v3-base
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+- precision
+- recall
+model-index:
+- name: deberta-v3-base-imdb
+  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. -->
+
+# deberta-v3-base-imdb
+
+This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3594
+- Accuracy: 0.9577
+- F1: 0.9579
+- Precision: 0.9530
+- Recall: 0.9629
+
+## 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: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     | Precision | Recall |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
+| 0.3108        | 1.0   | 12500 | 0.2634          | 0.9530   | 0.9529 | 0.9557    | 0.9502 |
+| 0.2322        | 2.0   | 25000 | 0.2629          | 0.9546   | 0.9552 | 0.9437    | 0.9670 |
+| 0.1119        | 3.0   | 37500 | 0.2944          | 0.9546   | 0.9550 | 0.9467    | 0.9634 |
+| 0.0292        | 4.0   | 50000 | 0.3694          | 0.9557   | 0.9564 | 0.9422    | 0.9710 |
+| 0.0191        | 5.0   | 62500 | 0.3594          | 0.9577   | 0.9579 | 0.9530    | 0.9629 |
+
+
+### Framework versions
+
+- Transformers 4.39.1
+- Pytorch 2.2.1+cu121
+- Datasets 2.18.0
+- Tokenizers 0.15.2

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