transformers tensorboard safetensors bert fill-mask generated_from_trainer base_model:bert-base-cased license:apache-2.0 autotrain_compatible endpoints_compatible region:us
---
license: apache-2.0
base_model: bert-base-cased
tags:
- generated_from_trainer
model-index:
- name: my_awesome_eli5_mlm_model
  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. -->

# my_awesome_eli5_mlm_model

This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.5349

## 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: 2e-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
- num_epochs: 25

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log        | 1.0   | 38   | 3.3747          |
| No log        | 2.0   | 76   | 3.1852          |
| No log        | 3.0   | 114  | 3.0839          |
| No log        | 4.0   | 152  | 3.1410          |
| No log        | 5.0   | 190  | 3.0394          |
| No log        | 6.0   | 228  | 3.0631          |
| No log        | 7.0   | 266  | 3.1484          |
| No log        | 8.0   | 304  | 2.7834          |
| No log        | 9.0   | 342  | 2.9527          |
| No log        | 10.0  | 380  | 3.2091          |
| No log        | 11.0  | 418  | 3.0497          |
| No log        | 12.0  | 456  | 2.7234          |
| No log        | 13.0  | 494  | 2.7865          |
| 2.8163        | 14.0  | 532  | 2.5425          |
| 2.8163        | 15.0  | 570  | 2.9351          |
| 2.8163        | 16.0  | 608  | 2.9367          |
| 2.8163        | 17.0  | 646  | 3.0570          |
| 2.8163        | 18.0  | 684  | 2.8902          |
| 2.8163        | 19.0  | 722  | 2.8285          |
| 2.8163        | 20.0  | 760  | 3.1220          |
| 2.8163        | 21.0  | 798  | 2.5891          |
| 2.8163        | 22.0  | 836  | 2.7217          |
| 2.8163        | 23.0  | 874  | 2.8660          |
| 2.8163        | 24.0  | 912  | 2.9048          |
| 2.8163        | 25.0  | 950  | 2.5349          |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
