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-v0.2
+  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-v0.2
+
+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: 0.2233
+- Accuracy: 0.9653
+- F1: 0.9654
+- Precision: 0.9637
+- Recall: 0.9670
+
+## 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: 10
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     | Precision | Recall |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
+| 0.2279        | 1.0   | 3125  | 0.1466          | 0.9603   | 0.9599 | 0.9693    | 0.9506 |
+| 0.2689        | 2.0   | 6250  | 0.1929          | 0.9550   | 0.9546 | 0.9626    | 0.9467 |
+| 0.1728        | 3.0   | 9375  | 0.1807          | 0.9584   | 0.9579 | 0.9697    | 0.9463 |
+| 0.1937        | 4.0   | 12500 | 0.1734          | 0.9435   | 0.9457 | 0.9102    | 0.9841 |
+| 0.2044        | 5.0   | 15625 | 0.2102          | 0.9510   | 0.9523 | 0.9272    | 0.9788 |
+| 0.0484        | 6.0   | 18750 | 0.2134          | 0.9593   | 0.9599 | 0.9448    | 0.9756 |
+| 0.0336        | 7.0   | 21875 | 0.2278          | 0.9610   | 0.9614 | 0.9524    | 0.9706 |
+| 0.0704        | 8.0   | 25000 | 0.2039          | 0.9648   | 0.9651 | 0.9581    | 0.9721 |
+| 0.0004        | 9.0   | 28125 | 0.2241          | 0.9656   | 0.9657 | 0.9640    | 0.9673 |
+| 0.0004        | 10.0  | 31250 | 0.2233          | 0.9653   | 0.9654 | 0.9637    | 0.9670 |
+
+
+### Framework versions
+
+- Transformers 4.39.2
+- Pytorch 2.2.0+cu121
+- Datasets 2.18.0
+- Tokenizers 0.15.2

model.safetensors

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