End of training

README.md

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+---
+license: mit
+base_model: microsoft/deberta-v3-large
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+- precision
+- recall
+model-index:
+- name: deberta-v3-large-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-large-imdb
+
+This model is a fine-tuned version of [microsoft/deberta-v3-large](https://huggingface.co/microsoft/deberta-v3-large) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1906
+- Accuracy: 0.9646
+- F1: 0.9645
+- Precision: 0.9679
+- Recall: 0.9610
+
+## 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: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_ratio: 0.2
+- num_epochs: 4
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     | Precision | Recall |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
+| 0.2471        | 1.0   | 3125  | 0.2004          | 0.9487   | 0.9474 | 0.9710    | 0.9250 |
+| 0.2029        | 2.0   | 6250  | 0.1715          | 0.9603   | 0.9600 | 0.9664    | 0.9537 |
+| 0.0631        | 3.0   | 9375  | 0.2049          | 0.9566   | 0.9555 | 0.9793    | 0.9329 |
+| 0.0432        | 4.0   | 12500 | 0.1906          | 0.9646   | 0.9645 | 0.9679    | 0.9610 |
+
+
+### Framework versions
+
+- Transformers 4.39.2
+- Pytorch 2.2.0+cu121
+- Datasets 2.18.0
+- Tokenizers 0.15.2

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