transformers pytorch bert license:apache-2.0 endpoints_compatible region:us
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license: apache-2.0
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## Cat Embeddings

A set of embedding model trained for study embedding quality vs model architecture (width/depth) given a size constraint (12M params).

- **cat-emb-2-128**: 2 layers/hidden size 128/4.4m
- **cat-emb-4-128**: 4 layers/H 128/4.8m
- **cat-emb-8-128**: 8 layers/H 128/5.6m
- **cat-emb-12-128**: 12 layers/H 128/6.4m
- **cat-emb-2-256**: 2 layers/H 256/9.7m
- **cat-emb-4-256**: 4 layers/H 256/11.3m

### Training

- stage 1: seq 192, batch size 2048, 50k steps, sentence pairs.
- stage 2: seq 512, batch size 64, 5k steps, sentence triplets.

### Perf

| MRL dim\Task | BIOSSES | SICK-R | STS12 | STS13 | STS14 | STS15 | STS16 | STSB | SummEval |
|-----|---------|--------|-------|-------|-------|-------|-------|------|----------|
| 128 | 0.7107  | 0.7126 | 0.6815| 0.7343| 0.7038| 0.8163| 0.7495| 0.7652| 0.2958   |
| 64  | 0.713   | 0.7123 | 0.6829| 0.7348| 0.7008| 0.813 | 0.7475| 0.7609| 0.2861   |
| 32  | 0.6714  | 0.7094 | 0.6847| 0.7345| 0.6911| 0.7989| 0.7385| 0.7545| 0.3106   |
| 16  | 0.6637  | 0.697  | 0.669 | 0.7096| 0.6665| 0.7589| 0.7183| 0.7307| 0.3164   |


