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--- |
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library_name: transformers |
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license: mit |
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base_model: microsoft/deberta-large |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: deberta-final |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# deberta-final |
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This model is a fine-tuned version of [microsoft/deberta-large](https://huggingface.co/microsoft/deberta-large) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- eval_loss: 0.4335 |
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- eval_accuracy: 0.8762 |
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- eval_f1: 0.8762 |
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- eval_runtime: 1227.0064 |
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- eval_samples_per_second: 85.273 |
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- eval_steps_per_second: 2.843 |
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- epoch: 2.6816 |
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- step: 26500 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 3e-05 |
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- train_batch_size: 30 |
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- eval_batch_size: 30 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 60 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 600 |
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- num_epochs: 7 |
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- mixed_precision_training: Native AMP |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.0 |
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- Datasets 3.0.0 |
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- Tokenizers 0.19.1 |
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