---
license: mit
base_model: gpt2-large
tags:
- generated_from_trainer
model-index:
- name: tiq
  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. -->

# tiq

This model is a fine-tuned version of [gpt2-large](https://huggingface.co/gpt2-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 5.5477

## 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: 8
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 200
- num_epochs: 1
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 6.2342        | 0.04  | 100  | 6.1857          |
| 5.7599        | 0.07  | 200  | 5.7751          |
| 5.7433        | 0.11  | 300  | 5.7142          |
| 5.6021        | 0.15  | 400  | 5.6776          |
| 5.5084        | 0.18  | 500  | 5.6349          |
| 5.3825        | 0.22  | 600  | 5.6201          |
| 5.6698        | 0.26  | 700  | 5.5831          |
| 5.4089        | 0.29  | 800  | 5.5687          |
| 5.601         | 0.33  | 900  | 5.5574          |
| 5.4708        | 0.37  | 1000 | 5.5555          |
| 5.5956        | 0.4   | 1100 | 5.5520          |
| 5.4704        | 0.44  | 1200 | 5.5494          |
| 5.4824        | 0.47  | 1300 | 5.5502          |
| 5.589         | 0.51  | 1400 | 5.5478          |
| 5.5612        | 0.55  | 1500 | 5.5456          |
| 5.4741        | 0.58  | 1600 | 5.5430          |
| 5.463         | 0.62  | 1700 | 5.5426          |
| 5.5071        | 0.66  | 1800 | 5.5424          |
| 5.5469        | 0.69  | 1900 | 5.5419          |
| 5.4266        | 0.73  | 2000 | 5.5428          |
| 5.4848        | 0.77  | 2100 | 5.5438          |
| 5.5069        | 0.8   | 2200 | 5.5446          |
| 5.5885        | 0.84  | 2300 | 5.5469          |
| 5.4484        | 0.88  | 2400 | 5.5462          |
| 5.3859        | 0.91  | 2500 | 5.5475          |
| 5.465         | 0.95  | 2600 | 5.5476          |
| 5.4355        | 0.99  | 2700 | 5.5477          |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.2.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2