---
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