pytorch tensorboard bert fill-mask transformers generated_from_trainer license:apache-2.0 model-index autotrain_compatible
---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: bert-base-uncased-2-finetuned-RRamicus
  results: []
---

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# bert-base-uncased-2-finetuned-RRamicus

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4784

## 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: 928
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 2.0341        | 1.0   | 1113  | 1.7515          |
| 1.7881        | 2.0   | 2226  | 1.6616          |
| 1.697         | 3.0   | 3339  | 1.6061          |
| 1.6328        | 4.0   | 4452  | 1.5662          |
| 1.5919        | 5.0   | 5565  | 1.5362          |
| 1.5602        | 6.0   | 6678  | 1.5193          |
| 1.5221        | 7.0   | 7791  | 1.4984          |
| 1.5135        | 8.0   | 8904  | 1.4898          |
| 1.4917        | 9.0   | 10017 | 1.4755          |
| 1.4859        | 10.0  | 11130 | 1.4671          |


### Framework versions

- Transformers 4.18.0
- Pytorch 1.10.0+cu111
- Datasets 2.1.0
- Tokenizers 0.12.1
