---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: 22_12_13_luther_blocks_xl_fp16_5ep
  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. -->

# 22_12_13_luther_blocks_xl_fp16_5ep

This model is a fine-tuned version of [malteos/gpt2-xl-wechsel-german](https://huggingface.co/malteos/gpt2-xl-wechsel-german) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.8833
- Accuracy: 0.4196

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.19  | 50   | 3.0276          | 0.3997   |
| No log        | 0.38  | 100  | 2.9185          | 0.4143   |
| No log        | 0.58  | 150  | 2.8846          | 0.4189   |
| No log        | 0.77  | 200  | 2.8833          | 0.4196   |
| 3.0309        | 0.96  | 250  | 2.8833          | 0.4196   |
| 3.0309        | 1.15  | 300  | 2.8833          | 0.4196   |
| 3.0309        | 1.35  | 350  | 2.8833          | 0.4196   |
| 3.0309        | 1.54  | 400  | 2.8833          | 0.4196   |
| 3.0309        | 1.73  | 450  | 2.8833          | 0.4196   |
| 2.8083        | 1.92  | 500  | 2.8833          | 0.4196   |
| 2.8083        | 2.12  | 550  | 2.8833          | 0.4196   |
| 2.8083        | 2.31  | 600  | 2.8833          | 0.4196   |
| 2.8083        | 2.5   | 650  | 2.8833          | 0.4196   |
| 2.8083        | 2.69  | 700  | 2.8833          | 0.4196   |
| 2.7992        | 2.88  | 750  | 2.8833          | 0.4196   |
| 2.7992        | 3.08  | 800  | 2.8833          | 0.4196   |
| 2.7992        | 3.27  | 850  | 2.8833          | 0.4196   |
| 2.7992        | 3.46  | 900  | 2.8833          | 0.4196   |
| 2.7992        | 3.65  | 950  | 2.8833          | 0.4196   |
| 2.7935        | 3.85  | 1000 | 2.8833          | 0.4196   |
| 2.7935        | 4.04  | 1050 | 2.8833          | 0.4196   |
| 2.7935        | 4.23  | 1100 | 2.8833          | 0.4196   |
| 2.7935        | 4.42  | 1150 | 2.8833          | 0.4196   |
| 2.7935        | 4.62  | 1200 | 2.8833          | 0.4196   |
| 2.8129        | 4.81  | 1250 | 2.8833          | 0.4196   |
| 2.8129        | 5.0   | 1300 | 2.8833          | 0.4196   |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.13.0
- Datasets 2.7.1
- Tokenizers 0.12.1