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super_chat_20260306214838_pfqf
3.36M parameter super_chat model — bpe-chat-4k tokenizer, 4L/192D/6H
Overview
3.36M
Parameters
5.4167
Final Loss
6.4987
Best Val Loss
225.1
Perplexity
1,689,600
Tokens Processed
0.5
Tokens/Param
40,291 tok/s
Avg Throughput
5m 33s
Training Time
Training Progress550 / 50,000 steps (1.1%)
Loss reduced by 35.1% from initial 8.3466
Dataset & Training
Domainsuper_chat
Tokenizerbpe-chat-4k
Total Iterations50,000
Batch Size12
Context Length256 tokens
Tokens per Batch3,072
Dataset Passes~4
Effective Tokens1,689,600
Training Pipeline
Warmupsteps 1–500
Learning rate warmup — model weights adjusting to data distribution
Loss: 8.347 → 5.424Linear LR warmup, gradient clipping
Training Metrics
Loss Curve
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Smoothed Loss
Perplexity
Learning Rate
Gradient Norm
Throughput (tok/s)
Timing Breakdown
No Telemetry
Model Architecture
Model Configuration
ArchitectureGPT (decoder-only transformer)
Parameters3.36M
Layers4
Embedding Dim192
Attention Heads6
Head Dim32
FFN Dim768
FFN Activationgelu
Vocab Size4,000
Context Length256 tokens
Dropout0
Training Configuration
Optimizeradamw
Learning Rate0.001
LR Min0.0001
LR ScheduleCosine decay
Warmup Steps500
Batch Size12
Grad Accum Steps2
Effective Batch24
Grad Clip1
Weight Decay0.1
Backendhelios
Tokenizerbpe-chat-4k
Seed42
Layer Structure
Token Embed
4,000×192
Pos Embed
256×192
Block 0
Attn+FFN
Block 1
Attn+FFN
Block 2
Attn+FFN
Block 3
Attn+FFN
LayerNorm
192
LM Head
192×4,000
Generated Samples
Step 0 — Mar 6, 2026 9:55 PM
Prompt: <|user|> Hello, how are you? <|assistant|>
<|user|> Hello, how are you? <|assistant|>m s an H AH H <|assistant|>Y
Checkpoints
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