transformers safetensors bert fill-mask generated_from_trainer base_model:bert-large-uncased license:apache-2.0 autotrain_compatible endpoints_compatible region:us
---
license: apache-2.0
base_model: bert-large-uncased
tags:
- generated_from_trainer
model-index:
- name: dbw-bert-large-1
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# dbw-bert-large-1

This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0728

## 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-07
- train_batch_size: 64
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 3.0555        | 0.36  | 200  | 3.2109          |
| 1.2673        | 0.71  | 400  | 1.0203          |
| 0.3153        | 1.07  | 600  | 0.2516          |
| 0.1461        | 1.42  | 800  | 0.1146          |
| 0.1046        | 1.78  | 1000 | 0.0854          |
| 0.0929        | 2.13  | 1200 | 0.0762          |
| 0.085         | 2.49  | 1400 | 0.0734          |
| 0.0881        | 2.84  | 1600 | 0.0728          |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
