---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased-rvl-cdip
  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. -->

# distilbert-base-uncased-rvl-cdip

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2055
- Accuracy: 0.7079

## 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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 15
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 48   | 2.4392          | 0.45     |
| No log        | 2.0   | 96   | 1.5529          | 0.5632   |
| No log        | 3.0   | 144  | 1.3164          | 0.6132   |
| No log        | 4.0   | 192  | 1.1269          | 0.6395   |
| No log        | 5.0   | 240  | 1.0145          | 0.7      |
| No log        | 6.0   | 288  | 1.0839          | 0.6816   |
| No log        | 7.0   | 336  | 1.1414          | 0.6868   |
| No log        | 8.0   | 384  | 1.1220          | 0.7053   |
| No log        | 9.0   | 432  | 1.1402          | 0.7105   |
| No log        | 10.0  | 480  | 1.1805          | 0.7132   |
| 0.8154        | 11.0  | 528  | 1.1923          | 0.7132   |
| 0.8154        | 12.0  | 576  | 1.2007          | 0.7079   |
| 0.8154        | 13.0  | 624  | 1.1973          | 0.7079   |
| 0.8154        | 14.0  | 672  | 1.2049          | 0.7105   |
| 0.8154        | 15.0  | 720  | 1.2055          | 0.7079   |


### Framework versions

- Transformers 4.36.0
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0