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

# children_bnc_rarity_all_no_cut

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: 4.3266

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|
| 6.7047        | 0.29  | 500   | 5.6398          |
| 5.3501        | 0.58  | 1000  | 5.2066          |
| 5.0056        | 0.88  | 1500  | 4.9588          |
| 4.7258        | 1.17  | 2000  | 4.8173          |
| 4.5734        | 1.46  | 2500  | 4.6948          |
| 4.4663        | 1.75  | 3000  | 4.5804          |
| 4.3402        | 2.05  | 3500  | 4.5071          |
| 4.1471        | 2.34  | 4000  | 4.4576          |
| 4.1137        | 2.63  | 4500  | 4.4027          |
| 4.0777        | 2.92  | 5000  | 4.3468          |
| 3.8629        | 3.22  | 5500  | 4.3449          |
| 3.8078        | 3.51  | 6000  | 4.3108          |
| 3.8044        | 3.8   | 6500  | 4.2763          |
| 3.7029        | 4.09  | 7000  | 4.2803          |
| 3.5324        | 4.39  | 7500  | 4.2741          |
| 3.5239        | 4.68  | 8000  | 4.2585          |
| 3.5091        | 4.97  | 8500  | 4.2454          |
| 3.3521        | 5.26  | 9000  | 4.2592          |
| 3.3357        | 5.56  | 9500  | 4.2584          |
| 3.3348        | 5.85  | 10000 | 4.2573          |


### Framework versions

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