safetensors generated_from_trainer base_model:distilbert-base-uncased license:apache-2.0 region:us
---
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: 21.1324
- Precision: 0.0411
- Recall: 0.0411
- F1: 0.0411
- Accuracy: 0.0411

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 21.2329       | 1.0   | 25   | 21.1260         | 0.0157    | 0.0157 | 0.0157 | 0.0157   |
| 18.2402       | 2.0   | 50   | 20.8705         | 0.0181    | 0.0181 | 0.0181 | 0.0181   |
| 15.7819       | 3.0   | 75   | 20.8017         | 0.0206    | 0.0206 | 0.0206 | 0.0206   |
| 13.5492       | 4.0   | 100  | 20.7470         | 0.0206    | 0.0206 | 0.0206 | 0.0206   |
| 11.836        | 5.0   | 125  | 20.7319         | 0.0254    | 0.0254 | 0.0254 | 0.0254   |
| 10.306        | 6.0   | 150  | 20.7540         | 0.0314    | 0.0314 | 0.0314 | 0.0314   |
| 9.0142        | 7.0   | 175  | 20.7665         | 0.0363    | 0.0363 | 0.0363 | 0.0363   |
| 7.991         | 8.0   | 200  | 20.8323         | 0.0363    | 0.0363 | 0.0363 | 0.0363   |
| 7.0936        | 9.0   | 225  | 20.9107         | 0.0387    | 0.0387 | 0.0387 | 0.0387   |
| 6.3742        | 10.0  | 250  | 20.9569         | 0.0399    | 0.0399 | 0.0399 | 0.0399   |
| 5.7236        | 11.0  | 275  | 20.9811         | 0.0375    | 0.0375 | 0.0375 | 0.0375   |
| 5.3262        | 12.0  | 300  | 21.0331         | 0.0435    | 0.0435 | 0.0435 | 0.0435   |
| 4.8222        | 13.0  | 325  | 21.0361         | 0.0387    | 0.0387 | 0.0387 | 0.0387   |
| 4.5049        | 14.0  | 350  | 21.0610         | 0.0363    | 0.0363 | 0.0363 | 0.0363   |
| 4.1877        | 15.0  | 375  | 21.0827         | 0.0387    | 0.0387 | 0.0387 | 0.0387   |
| 3.9705        | 16.0  | 400  | 21.1020         | 0.0435    | 0.0435 | 0.0435 | 0.0435   |
| 3.8091        | 17.0  | 425  | 21.0863         | 0.0435    | 0.0435 | 0.0435 | 0.0435   |
| 3.5978        | 18.0  | 450  | 21.1236         | 0.0447    | 0.0447 | 0.0447 | 0.0447   |
| 3.5991        | 19.0  | 475  | 21.1211         | 0.0435    | 0.0435 | 0.0435 | 0.0435   |
| 3.5433        | 20.0  | 500  | 21.1236         | 0.0435    | 0.0435 | 0.0435 | 0.0435   |


### Framework versions

- Transformers 4.39.1
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
