End of training

README.md

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+---
+license: mit
+base_model: microsoft/deberta-v2-xxlarge
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+- precision
+- recall
+model-index:
+- name: deberta-v2-xxl-imdb-v0.1
+  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-v2-xxl-imdb-v0.1
+
+This model is a fine-tuned version of [microsoft/deberta-v2-xxlarge](https://huggingface.co/microsoft/deberta-v2-xxlarge) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1684
+- Accuracy: 0.9708
+- F1: 0.9710
+- Precision: 0.9669
+- Recall: 0.9750
+
+## 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: cosine
+- lr_scheduler_warmup_ratio: 0.2
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     | Precision | Recall |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
+| 0.0607        | 1.0   | 6250  | 0.2211          | 0.9616   | 0.9611 | 0.9738    | 0.9487 |
+| 0.3056        | 2.0   | 12500 | 0.1855          | 0.9662   | 0.9658 | 0.9770    | 0.9548 |
+| 0.0502        | 3.0   | 18750 | 0.1790          | 0.9696   | 0.9697 | 0.9668    | 0.9726 |
+| 0.2397        | 4.0   | 25000 | 0.1741          | 0.9705   | 0.9707 | 0.9634    | 0.9782 |
+| 0.1207        | 5.0   | 31250 | 0.1662          | 0.9708   | 0.9708 | 0.9713    | 0.9702 |
+| 0.0637        | 6.0   | 37500 | 0.1718          | 0.9707   | 0.9707 | 0.9710    | 0.9703 |
+| 0.3034        | 7.0   | 43750 | 0.1687          | 0.9706   | 0.9707 | 0.9670    | 0.9745 |
+| 0.0013        | 8.0   | 50000 | 0.1683          | 0.9708   | 0.9709 | 0.9668    | 0.9751 |
+| 0.0543        | 9.0   | 56250 | 0.1683          | 0.9707   | 0.9708 | 0.9667    | 0.9750 |
+| 0.1015        | 10.0  | 62500 | 0.1684          | 0.9708   | 0.9710 | 0.9669    | 0.9750 |
+
+
+### Framework versions
+
+- Transformers 4.39.2
+- Pytorch 2.2.1+cu121
+- Datasets 2.18.0
+- Tokenizers 0.15.2

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