---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- wikitext
metrics:
- accuracy
model-index:
- name: distilbert_add_pre-training-dim-96
  results:
  - task:
      name: Masked Language Modeling
      type: fill-mask
    dataset:
      name: wikitext wikitext-103-raw-v1
      type: wikitext
      config: wikitext-103-raw-v1
      split: validation
      args: wikitext-103-raw-v1
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.14942141332434558
---

<!-- 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_add_pre-training-dim-96

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the wikitext wikitext-103-raw-v1 dataset.
It achieves the following results on the evaluation set:
- Loss: 6.6092
- Accuracy: 0.1494

## 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: 64
- eval_batch_size: 64
- seed: 10
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 15
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 14.685        | 1.0   | 3573  | 9.3922          | 0.1240   |
| 8.0255        | 2.0   | 7146  | 7.1510          | 0.1315   |
| 7.0152        | 3.0   | 10719 | 6.7861          | 0.1482   |
| 6.8127        | 4.0   | 14292 | 6.7053          | 0.1493   |
| 6.74          | 5.0   | 17865 | 6.6695          | 0.1474   |
| 6.7067        | 6.0   | 21438 | 6.6431          | 0.1491   |
| 6.6871        | 7.0   | 25011 | 6.6204          | 0.1483   |
| 6.6748        | 8.0   | 28584 | 6.6250          | 0.1473   |
| 6.6649        | 9.0   | 32157 | 6.6108          | 0.1486   |
| 6.6596        | 10.0  | 35730 | 6.6140          | 0.1497   |
| 6.6536        | 11.0  | 39303 | 6.6067          | 0.1493   |
| 6.6483        | 12.0  | 42876 | 6.6140          | 0.1489   |
| 6.6463        | 13.0  | 46449 | 6.6096          | 0.1484   |
| 6.6434        | 14.0  | 50022 | 6.5570          | 0.1526   |
| 6.6414        | 15.0  | 53595 | 6.5836          | 0.1526   |


### Framework versions

- Transformers 4.26.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.9.0
- Tokenizers 0.13.2