---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: tiny-mlm-wikitext-custom-tokenizer
  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. -->

# tiny-mlm-wikitext-custom-tokenizer

This model is a fine-tuned version of [google/bert_uncased_L-2_H-128_A-2](https://huggingface.co/google/bert_uncased_L-2_H-128_A-2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 6.4940

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- num_epochs: 200

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 8.1543        | 0.4   | 500   | 7.6501          |
| 7.4342        | 0.8   | 1000  | 7.5531          |
| 7.3656        | 1.2   | 1500  | nan             |
| 7.2844        | 1.6   | 2000  | 7.4543          |
| 7.2621        | 2.0   | 2500  | 7.4480          |
| 7.1668        | 2.4   | 3000  | 7.3456          |
| 7.1874        | 2.8   | 3500  | 7.3750          |
| 7.1284        | 3.2   | 4000  | nan             |
| 7.1041        | 3.6   | 4500  | 7.2361          |
| 7.0693        | 4.0   | 5000  | 7.2836          |
| 7.0604        | 4.4   | 5500  | 7.2521          |
| 6.993         | 4.8   | 6000  | 7.2082          |
| 7.0014        | 5.2   | 6500  | 7.1960          |
| 6.9607        | 5.6   | 7000  | 7.1971          |
| 6.9514        | 6.0   | 7500  | nan             |
| 6.9524        | 6.4   | 8000  | 7.0977          |
| 6.8999        | 6.8   | 8500  | 7.0787          |
| 6.8471        | 7.2   | 9000  | 7.1168          |
| 6.8511        | 7.6   | 9500  | 7.0589          |
| 6.8111        | 8.0   | 10000 | 7.0058          |
| 6.8131        | 8.4   | 10500 | 7.0089          |
| 6.717         | 8.8   | 11000 | 6.9681          |
| 6.7024        | 9.2   | 11500 | 6.9542          |
| 6.7567        | 9.6   | 12000 | 6.9008          |
| 6.7025        | 10.0  | 12500 | 6.8863          |
| 6.6509        | 10.4  | 13000 | 6.8794          |
| 6.6151        | 10.8  | 13500 | 6.8888          |
| 6.6348        | 11.2  | 14000 | 6.8106          |
| 6.6061        | 11.6  | 14500 | 6.8399          |
| 6.5637        | 12.0  | 15000 | 6.8289          |
| 6.5526        | 12.4  | 15500 | 6.7866          |
| 6.4899        | 12.8  | 16000 | 6.7108          |
| 6.5106        | 13.2  | 16500 | 6.7707          |
| 6.5022        | 13.6  | 17000 | 6.7289          |
| 6.429         | 14.0  | 17500 | 6.6883          |
| 6.4342        | 14.4  | 18000 | 6.6669          |
| 6.4385        | 14.8  | 18500 | 6.6722          |
| 6.4328        | 15.2  | 19000 | 6.6867          |
| 6.3802        | 15.6  | 19500 | 6.6403          |
| 6.375         | 16.0  | 20000 | 6.6141          |
| 6.332         | 16.4  | 20500 | 6.6759          |
| 6.3237        | 16.8  | 21000 | 6.5960          |
| 6.3551        | 17.2  | 21500 | 6.5551          |
| 6.2918        | 17.6  | 22000 | nan             |
| 6.3           | 18.0  | 22500 | 6.5744          |
| 6.2555        | 18.4  | 23000 | 6.5212          |
| 6.2569        | 18.8  | 23500 | 6.5515          |
| 6.2658        | 19.2  | 24000 | 6.5763          |
| 6.2205        | 19.6  | 24500 | 6.4887          |
| 6.2022        | 20.0  | 25000 | 6.4955          |
| 6.1881        | 20.4  | 25500 | 6.4849          |
| 6.1479        | 20.8  | 26000 | 6.4727          |
| 6.1805        | 21.2  | 26500 | 6.4253          |
| 6.1439        | 21.6  | 27000 | 6.4397          |
| 6.1332        | 22.0  | 27500 | 6.4876          |
| 6.1379        | 22.4  | 28000 | 6.4940          |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu116
- Datasets 2.8.1.dev0
- Tokenizers 0.13.2