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---
base_model: t5-small
tags: [trm, act, recursive, text-generation, wikitext]
metrics: [loss, lm_loss, ponder_loss, perplexity_lm]
---
# TRM-Text1 (ACT)
**TRM-Text1 (ACT)** is a causal language model based on a **Tiny Recursive Reasoning Model (TRM)** with **Adaptive Computation Time (ACT)** for per-token variable depth.
- **Architecture:** TRM (causal) + ACT halting
- **Training Data:** wikitext-103-raw-v1
- **Tokenizer:** t5-small (SentencePiece)
- **Vocab Size:** 32100
- **Objective:** Causal Language Modeling (next-token)
- **Seq Len:** 1024
Note: This model uses the T5 SentencePiece tokenizer. Perplexity numbers on WT103
reported here are not directly comparable to GPT-2 BPE-based PPLs.
### Latest Performance (Epoch 1)
- **Validation Loss**: 4.8248
- **Validation LM Loss**: 4.8149
- **Validation Ponder Loss**: 1.0064
- **Validation Perplexity (LM-only)**: 123.34
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