---
tags:
- generated_from_trainer
datasets:
- generator
model-index:
- name: bert-dp-4
  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-dp-4

This model is a fine-tuned version of [](https://huggingface.co/) on the generator dataset.
It achieves the following results on the evaluation set:
- Loss: 6.7082

## 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: 0.0005
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 1000
- num_epochs: 40
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 6.3445        | 1.89  | 1000  | 5.9292          |
| 5.8327        | 3.78  | 2000  | 5.8495          |
| 6.5089        | 5.67  | 3000  | 6.7228          |
| 6.7256        | 7.56  | 4000  | 6.7197          |
| 6.7194        | 9.45  | 5000  | 6.7135          |
| 6.7174        | 11.34 | 6000  | 6.7132          |
| 6.7114        | 13.23 | 7000  | 6.7119          |
| 6.7166        | 15.12 | 8000  | 6.7129          |
| 6.7109        | 17.01 | 9000  | 6.7107          |
| 6.7112        | 18.9  | 10000 | 6.7134          |
| 6.7125        | 20.79 | 11000 | 6.7090          |
| 6.7099        | 22.68 | 12000 | 6.7085          |
| 6.7084        | 24.57 | 13000 | 6.7069          |
| 6.7066        | 26.47 | 14000 | 6.7063          |
| 6.7083        | 28.36 | 15000 | 6.7037          |
| 6.7062        | 30.25 | 16000 | 6.7044          |
| 6.705         | 32.14 | 17000 | 6.7022          |
| 6.7041        | 34.03 | 18000 | 6.7058          |
| 6.7031        | 35.92 | 19000 | 6.7055          |
| 6.7031        | 37.81 | 20000 | 6.7067          |
| 6.7039        | 39.7  | 21000 | 6.7082          |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.11.0+cu113
- Datasets 2.13.0
- Tokenizers 0.13.3