README.md

---
license: apache-2.0
datasets:
- HuggingFaceTB/smollm-corpus
language:
- en
library_name: transformers
pipeline_tag: text2text-generation
tags:
- fineweb
- t5
---


- 1024 ctx
- SiLU activations
- `fineweb-edu-dedup` split of `HuggingFaceTB/smollm-corpus`

## details


1. Model:
   - Dropout rate: 0.0
   - Activations: `silu`, `gated-silu`
   - torch compile: true

2. Data processing:
   - Input length: 1024
   - MLM probability: 0.15

3. Optimization:
   - Optimizer: AdamW with scaling
   - Base learning rate: 0.008
   - Batch size: 120
   - Total training steps: 80,000
   - Warmup steps: 10,000
   - Learning rate scheduler: Cosine
   - Weight decay: 0.0001
   - Gradient clipping: 1.0
   - Gradient accumulation steps: 24
   - Final cosine learning rate: 1e-5

4. Hardware utilization:
   - Device: GPU
   - Precision: bfloat16, tf32

## plots


training loss  

![loss](./checkpoints/loss_over_steps.png)


grad norm 

![grad](./checkpoints/grad_l2_over_steps.png)


weights norm


![weights](./checkpoints/weights_l2_over_steps.png)


---