---
license: mit
tags:
- generated_from_trainer
datasets:
- generator
model-index:
- name: cbt-len
  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. -->

# cbt-len

This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on the generator dataset.
It achieves the following results on the evaluation set:
- Loss: 4.0441

## 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: 0.0005
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 1000
- num_epochs: 6
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 6.3484        | 0.29  | 500   | 5.3167          |
| 5.0338        | 0.58  | 1000  | 4.8930          |
| 4.7064        | 0.87  | 1500  | 4.6570          |
| 4.4436        | 1.16  | 2000  | 4.5103          |
| 4.292         | 1.45  | 2500  | 4.3926          |
| 4.185         | 1.74  | 3000  | 4.2824          |
| 4.0816        | 2.03  | 3500  | 4.2049          |
| 3.8852        | 2.32  | 4000  | 4.1665          |
| 3.8585        | 2.61  | 4500  | 4.1129          |
| 3.8118        | 2.9   | 5000  | 4.0589          |
| 3.6437        | 3.18  | 5500  | 4.0555          |
| 3.5738        | 3.47  | 6000  | 4.0265          |
| 3.5595        | 3.76  | 6500  | 3.9952          |
| 3.4943        | 4.05  | 7000  | 3.9873          |
| 3.3042        | 4.34  | 7500  | 3.9849          |
| 3.2977        | 4.63  | 8000  | 3.9721          |
| 3.2891        | 4.92  | 8500  | 3.9592          |
| 3.1673        | 5.21  | 9000  | 3.9698          |
| 3.1192        | 5.5   | 9500  | 3.9685          |
| 3.1173        | 5.79  | 10000 | 3.9678          |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.11.0+cu113
- Datasets 2.13.0
- Tokenizers 0.13.3