---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
base_model: gpt2
model-index:
- name: js-fake-bach-epochs50
  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. -->

# js-fake-bach-epochs50

This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9888
- Accuracy: 0.0005

## 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: 0.0006058454513356471
- train_batch_size: 16
- eval_batch_size: 32
- seed: 1
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.01
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.3512        | 1.25  | 315   | 0.8371          | 0.0003   |
| 0.8149        | 2.51  | 630   | 0.7684          | 0.0006   |
| 0.7601        | 3.76  | 945   | 0.7187          | 0.0004   |
| 0.7186        | 5.02  | 1260  | 0.6903          | 0.0002   |
| 0.679         | 6.27  | 1575  | 0.6563          | 0.0005   |
| 0.6419        | 7.53  | 1890  | 0.6292          | 0.0001   |
| 0.6073        | 8.78  | 2205  | 0.5949          | 0.0006   |
| 0.575         | 10.04 | 2520  | 0.5828          | 0.0001   |
| 0.5425        | 11.29 | 2835  | 0.5696          | 0.0003   |
| 0.5174        | 12.55 | 3150  | 0.5609          | 0.0007   |
| 0.4933        | 13.8  | 3465  | 0.5576          | 0.0004   |
| 0.4696        | 15.06 | 3780  | 0.5661          | 0.0002   |
| 0.4423        | 16.31 | 4095  | 0.5708          | 0.0007   |
| 0.4196        | 17.57 | 4410  | 0.5780          | 0.0006   |
| 0.398         | 18.82 | 4725  | 0.5820          | 0.0009   |
| 0.374         | 20.08 | 5040  | 0.6099          | 0.0003   |
| 0.3452        | 21.33 | 5355  | 0.6230          | 0.0006   |
| 0.3256        | 22.59 | 5670  | 0.6386          | 0.0005   |
| 0.3047        | 23.84 | 5985  | 0.6462          | 0.0003   |
| 0.2812        | 25.1  | 6300  | 0.6789          | 0.0003   |
| 0.2582        | 26.35 | 6615  | 0.7053          | 0.0007   |
| 0.2406        | 27.61 | 6930  | 0.7199          | 0.0006   |
| 0.2237        | 28.86 | 7245  | 0.7399          | 0.0006   |
| 0.204         | 30.12 | 7560  | 0.7729          | 0.0006   |
| 0.1873        | 31.37 | 7875  | 0.7960          | 0.0004   |
| 0.1725        | 32.63 | 8190  | 0.8231          | 0.0005   |
| 0.1609        | 33.88 | 8505  | 0.8493          | 0.0004   |
| 0.1479        | 35.14 | 8820  | 0.8707          | 0.0003   |
| 0.1361        | 36.39 | 9135  | 0.8931          | 0.0003   |
| 0.1273        | 37.65 | 9450  | 0.9095          | 0.0003   |
| 0.12          | 38.9  | 9765  | 0.9339          | 0.0005   |
| 0.1129        | 40.16 | 10080 | 0.9444          | 0.0004   |
| 0.1062        | 41.41 | 10395 | 0.9626          | 0.0006   |
| 0.1027        | 42.67 | 10710 | 0.9669          | 0.0006   |
| 0.0994        | 43.92 | 11025 | 0.9713          | 0.0005   |
| 0.0955        | 45.18 | 11340 | 0.9830          | 0.0005   |
| 0.0939        | 46.43 | 11655 | 0.9855          | 0.0005   |
| 0.0924        | 47.69 | 11970 | 0.9884          | 0.0005   |
| 0.0916        | 48.94 | 12285 | 0.9888          | 0.0005   |


### Framework versions

- Transformers 4.29.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3