End of training

README.md

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+---
+library_name: transformers
+license: mit
+base_model: microsoft/deberta-large
+tags:
+- generated_from_trainer
+model-index:
+- name: deberta-final
+  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-final
+
+This model is a fine-tuned version of [microsoft/deberta-large](https://huggingface.co/microsoft/deberta-large) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- eval_loss: 0.4335
+- eval_accuracy: 0.8762
+- eval_f1: 0.8762
+- eval_runtime: 1227.0064
+- eval_samples_per_second: 85.273
+- eval_steps_per_second: 2.843
+- epoch: 2.6816
+- step: 26500
+
+## 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: 3e-05
+- train_batch_size: 30
+- eval_batch_size: 30
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 60
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 600
+- num_epochs: 7
+- mixed_precision_training: Native AMP
+
+### Framework versions
+
+- Transformers 4.44.2
+- Pytorch 2.4.0
+- Datasets 3.0.0
+- Tokenizers 0.19.1

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