---
license: mit
library_name: transformers
---
# MidTrainingCheckpoint

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<div align="center">
  <img src="figures/fig1.png" width="60%" alt="MidTrainingCheckpoint" />
</div>
<hr>

## 1. Introduction

MidTrainingCheckpoint is a snapshot taken at the midpoint of our training run. It captures the model state at step 500, providing a useful reference for studying training dynamics.

<p align="center">
  <img width="80%" src="figures/fig3.png">
</p>

This checkpoint is particularly useful for:
- Comparing with earlier and later checkpoints
- Understanding the training trajectory
- Performing intermediate model analysis

## 2. Model Details

| Property | Value |
|---|---|
| Architecture | BERT |
| Training Steps | 500 |
| Checkpoint Name | step_500 |
| Purpose | Mid-training reference |

## 3. Usage

```python
from transformers import AutoModel

model = AutoModel.from_pretrained("MidTraining-Checkpoint")
```

## 4. License
[MIT License](LICENSE)

## 5. Contact
Open an issue on GitHub.