---
tags:
- generated_from_trainer
model-index:
- name: Bert-MLM
  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. -->

# Bert-MLM

This model is a fine-tuned version of [](https://huggingface.co/) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 7.7544

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 1000

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log        | 0.02  | 50   | 9.3840          |
| 9.3687        | 0.03  | 100  | 8.6014          |
| 9.3687        | 0.05  | 150  | 8.2440          |
| 8.0254        | 0.06  | 200  | 8.0843          |
| 8.0254        | 0.08  | 250  | 8.0234          |
| 7.8649        | 0.09  | 300  | 7.9828          |
| 7.8649        | 0.11  | 350  | 7.9550          |
| 7.732         | 0.12  | 400  | 7.9101          |
| 7.732         | 0.14  | 450  | 7.8946          |
| 7.6192        | 0.15  | 500  | 7.8525          |
| 7.6192        | 0.17  | 550  | 7.8461          |
| 7.6378        | 0.18  | 600  | 7.8285          |
| 7.6378        | 0.2   | 650  | 7.8182          |
| 7.6338        | 0.22  | 700  | 7.7917          |
| 7.6338        | 0.23  | 750  | nan             |
| 7.5994        | 0.25  | 800  | 7.7837          |
| 7.5994        | 0.26  | 850  | 7.7596          |
| 7.5323        | 0.28  | 900  | 7.7634          |
| 7.5323        | 0.29  | 950  | 7.7750          |
| 7.5914        | 0.31  | 1000 | 7.7544          |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.2+cu118
- Datasets 2.16.0
- Tokenizers 0.15.0