File size: 1,124 Bytes
07740c5 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 | ---
license: mit
library_name: transformers
---
# MidTrainingCheckpoint
<!-- markdownlint-disable first-line-h1 -->
<!-- markdownlint-disable html -->
<!-- markdownlint-disable no-duplicate-header -->
<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.
|