---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: BERTModified-rawbert-finetuned-wikitext-test
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# BERTModified-rawbert-finetuned-wikitext-test

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 21.0426
- Precision: 0.0375
- Recall: 0.0375
- F1: 0.0375
- Accuracy: 0.0375

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 21.2097       | 1.0   | 25   | 21.0754         | 0.0157    | 0.0157 | 0.0157 | 0.0157   |
| 18.2793       | 2.0   | 50   | 20.8093         | 0.0133    | 0.0133 | 0.0133 | 0.0133   |
| 15.8444       | 3.0   | 75   | 20.6771         | 0.0157    | 0.0157 | 0.0157 | 0.0157   |
| 13.5759       | 4.0   | 100  | 20.6509         | 0.0218    | 0.0218 | 0.0218 | 0.0218   |
| 11.8523       | 5.0   | 125  | 20.6608         | 0.0230    | 0.0230 | 0.0230 | 0.0230   |
| 10.2973       | 6.0   | 150  | 20.6500         | 0.0242    | 0.0242 | 0.0242 | 0.0242   |
| 9.0372        | 7.0   | 175  | 20.7158         | 0.0266    | 0.0266 | 0.0266 | 0.0266   |
| 7.9788        | 8.0   | 200  | 20.7644         | 0.0290    | 0.0290 | 0.0290 | 0.0290   |
| 7.0864        | 9.0   | 225  | 20.7891         | 0.0278    | 0.0278 | 0.0278 | 0.0278   |
| 6.3465        | 10.0  | 250  | 20.8286         | 0.0302    | 0.0302 | 0.0302 | 0.0302   |
| 5.6973        | 11.0  | 275  | 20.8867         | 0.0351    | 0.0351 | 0.0351 | 0.0351   |
| 5.2951        | 12.0  | 300  | 20.9121         | 0.0363    | 0.0363 | 0.0363 | 0.0363   |
| 4.8066        | 13.0  | 325  | 20.9479         | 0.0375    | 0.0375 | 0.0375 | 0.0375   |
| 4.4862        | 14.0  | 350  | 21.0011         | 0.0351    | 0.0351 | 0.0351 | 0.0351   |
| 4.1891        | 15.0  | 375  | 21.0011         | 0.0363    | 0.0363 | 0.0363 | 0.0363   |
| 3.9551        | 16.0  | 400  | 21.0193         | 0.0423    | 0.0423 | 0.0423 | 0.0423   |
| 3.7954        | 17.0  | 425  | 21.0099         | 0.0351    | 0.0351 | 0.0351 | 0.0351   |
| 3.5836        | 18.0  | 450  | 21.0166         | 0.0411    | 0.0411 | 0.0411 | 0.0411   |
| 3.5873        | 19.0  | 475  | 21.0315         | 0.0399    | 0.0399 | 0.0399 | 0.0399   |
| 3.5297        | 20.0  | 500  | 21.0524         | 0.0387    | 0.0387 | 0.0387 | 0.0387   |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2