---
library_name: transformers
tags:
- generated_from_trainer
datasets:
- tiny_shakespeare
model-index:
- name: tinyshakespeare-13m
  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. -->

# tinyshakespeare-13m

This model is a fine-tuned version of [](https://huggingface.co/) on the tiny_shakespeare dataset.
It achieves the following results on the evaluation set:
- Loss: 4.9693

## 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: 0.0003
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 40
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log        | 1.0   | 32   | 7.3043          |
| 7.7103        | 2.0   | 64   | 5.9158          |
| 7.7103        | 3.0   | 96   | 5.6154          |
| 5.8675        | 4.0   | 128  | 5.3680          |
| 5.4479        | 5.0   | 160  | 5.2088          |
| 5.4479        | 6.0   | 192  | 5.1126          |
| 5.1825        | 7.0   | 224  | 5.0313          |
| 4.9945        | 8.0   | 256  | 4.9771          |
| 4.9945        | 9.0   | 288  | 4.9379          |
| 4.8838        | 10.0  | 320  | 4.9208          |
| 4.7883        | 11.0  | 352  | 4.8985          |
| 4.7883        | 12.0  | 384  | 4.8766          |
| 4.7261        | 13.0  | 416  | 4.8631          |
| 4.7261        | 14.0  | 448  | 4.8617          |
| 4.6621        | 15.0  | 480  | 4.8445          |
| 4.5955        | 16.0  | 512  | 4.8370          |
| 4.5955        | 17.0  | 544  | 4.8295          |
| 4.52          | 18.0  | 576  | 4.8215          |
| 4.4819        | 19.0  | 608  | 4.8278          |
| 4.4819        | 20.0  | 640  | 4.8169          |
| 4.4415        | 21.0  | 672  | 4.8252          |
| 4.3929        | 22.0  | 704  | 4.8199          |
| 4.3929        | 23.0  | 736  | 4.8243          |
| 4.3438        | 24.0  | 768  | 4.8340          |
| 4.3117        | 25.0  | 800  | 4.8309          |
| 4.3117        | 26.0  | 832  | 4.8410          |
| 4.2626        | 27.0  | 864  | 4.8439          |
| 4.2626        | 28.0  | 896  | 4.8437          |
| 4.2404        | 29.0  | 928  | 4.8404          |
| 4.1957        | 30.0  | 960  | 4.8540          |
| 4.1957        | 31.0  | 992  | 4.8560          |
| 4.1681        | 32.0  | 1024 | 4.8653          |
| 4.1441        | 33.0  | 1056 | 4.8725          |
| 4.1441        | 34.0  | 1088 | 4.8770          |
| 4.1097        | 35.0  | 1120 | 4.8798          |
| 4.0823        | 36.0  | 1152 | 4.8884          |
| 4.0823        | 37.0  | 1184 | 4.8869          |
| 4.0783        | 38.0  | 1216 | 4.8925          |
| 4.0783        | 39.0  | 1248 | 4.8948          |
| 4.0641        | 40.0  | 1280 | 4.8941          |


### Framework versions

- Transformers 4.57.1
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.22.1