End of training

README.md

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+---
+library_name: transformers
+language:
+- en
+license: mit
+base_model: microsoft/deberta-base
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: deberta-base-tweet-sentiment
+  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-base-tweet-sentiment
+
+This model is a fine-tuned version of [microsoft/deberta-base](https://huggingface.co/microsoft/deberta-base) on the Twitter Sentiment Datasets dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4842
+- Accuracy: 0.8019
+
+## 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: 1.5e-05
+- train_batch_size: 64
+- eval_batch_size: 64
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 128
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 500
+- num_epochs: 5
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
+|:-------------:|:------:|:----:|:---------------:|:--------:|
+| 0.8569        | 0.9985 | 332  | 0.5507          | 0.7729   |
+| 0.5439        | 2.0    | 665  | 0.5021          | 0.7947   |
+| 0.4502        | 2.9985 | 997  | 0.4842          | 0.8019   |
+| 0.3801        | 4.0    | 1330 | 0.5064          | 0.8013   |
+| 0.3387        | 4.9925 | 1660 | 0.5141          | 0.8057   |
+
+
+### Framework versions
+
+- Transformers 4.44.2
+- Pytorch 2.4.1+cu121
+- Datasets 3.0.1
+- Tokenizers 0.19.1

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