---
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert-large-uncased_finetuning_distillation
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# bert-large-uncased_finetuning_distillation

This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4721
- Accuracy: 0.8352

## 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: 0.0001
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 6

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.7395        | 1.39  | 500  | 0.8593          | 0.6847   |
| 0.6019        | 2.78  | 1000 | 0.5655          | 0.7949   |
| 0.3085        | 4.17  | 1500 | 0.4899          | 0.8293   |
| 0.1631        | 5.56  | 2000 | 0.4558          | 0.8475   |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1