deberta-final
This model is a fine-tuned version of 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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Model tree for Aadithyak/deberta-final
Base model
microsoft/deberta-large