transformers tensorboard safetensors beit image-classification generated_from_trainer base_model:microsoft/dit-base-finetuned-rvlcdip autotrain_compatible endpoints_compatible region:us
---
base_model: microsoft/dit-base-finetuned-rvlcdip
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: dit-base-finetuned-rvlcdip-finetuned-custom-first
  results: []
---

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# dit-base-finetuned-rvlcdip-finetuned-custom-first

This model is a fine-tuned version of [microsoft/dit-base-finetuned-rvlcdip](https://huggingface.co/microsoft/dit-base-finetuned-rvlcdip) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0567
- Accuracy: 0.9949

## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.3686        | 1.0   | 79   | 0.2356          | 0.9746   |
| 0.0891        | 2.0   | 158  | 0.0792          | 0.9936   |
| 0.0652        | 3.0   | 237  | 0.0567          | 0.9949   |


### Framework versions

- Transformers 4.38.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
