---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: tiny-mlm-glue-qnli-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-glue-qnli-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: 6.2339

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|
| 7.9951        | 0.4   | 500   | 7.3315          |
| 7.1282        | 0.8   | 1000  | 7.2457          |
| 7.0402        | 1.2   | 1500  | 7.2104          |
| 6.9634        | 1.6   | 2000  | 7.1415          |
| 6.9383        | 2.0   | 2500  | 7.0838          |
| 6.8365        | 2.4   | 3000  | 7.0031          |
| 6.7812        | 2.8   | 3500  | 6.9679          |
| 6.6959        | 3.2   | 4000  | 6.9121          |
| 6.6423        | 3.6   | 4500  | 6.8421          |
| 6.5766        | 4.0   | 5000  | 6.8474          |
| 6.5676        | 4.4   | 5500  | 6.8089          |
| 6.4728        | 4.8   | 6000  | 6.7246          |
| 6.5008        | 5.2   | 6500  | 6.7049          |
| 6.4367        | 5.6   | 7000  | 6.6539          |
| 6.4016        | 6.0   | 7500  | 6.6268          |
| 6.4063        | 6.4   | 8000  | 6.6038          |
| 6.3836        | 6.8   | 8500  | 6.5452          |
| 6.3576        | 7.2   | 9000  | 6.5932          |
| 6.2768        | 7.6   | 9500  | 6.5443          |
| 6.3002        | 8.0   | 10000 | 6.5018          |
| 6.304         | 8.4   | 10500 | 6.5263          |
| 6.2123        | 8.8   | 11000 | 6.4739          |
| 6.2015        | 9.2   | 11500 | 6.4407          |
| 6.1809        | 9.6   | 12000 | 6.4371          |
| 6.1624        | 10.0  | 12500 | 6.4379          |
| 6.1831        | 10.4  | 13000 | 6.3897          |
| 6.163         | 10.8  | 13500 | 6.4086          |
| 6.0881        | 11.2  | 14000 | 6.3902          |
| 6.0474        | 11.6  | 14500 | 6.3229          |
| 6.0454        | 12.0  | 15000 | 6.2995          |
| 6.0491        | 12.4  | 15500 | 6.3559          |
| 6.0045        | 12.8  | 16000 | 6.2820          |
| 6.043         | 13.2  | 16500 | 6.3260          |
| 5.9485        | 13.6  | 17000 | 6.2554          |
| 5.9513        | 14.0  | 17500 | 6.2668          |
| 5.9501        | 14.4  | 18000 | 6.2396          |
| 5.9882        | 14.8  | 18500 | 6.2655          |
| 5.9311        | 15.2  | 19000 | 6.1839          |
| 5.9662        | 15.6  | 19500 | 6.1942          |
| 5.9328        | 16.0  | 20000 | 6.2425          |
| 5.8984        | 16.4  | 20500 | 6.2339          |


### Framework versions

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