add small-scaled model for audio tagging (#1604)

egs/audioset/AT/RESULTS.md

@@ -5,6 +5,8 @@ See <https://github.com/k2-fsa/icefall/pull/1421> for more details
 
 [zipformer](./zipformer)
 
+#### normal-scaled model, number of model parameters: 65549011, i.e., 65.55 M
+
 You can find a pretrained model, training logs, decoding logs, and decoding results at:
 <https://huggingface.co/marcoyang/icefall-audio-tagging-audioset-zipformer-2024-03-12#/>
 
@@ -42,3 +44,52 @@ python zipformer/evaluate.py \
     --exp-dir zipformer/exp_at_as_full \
     --max-duration 500
 ```
+
+
+#### small-scaled model, number of model parameters: 22125218, i.e., 22.13 M
+
+You can find a pretrained model, training logs, decoding logs, and decoding results at:
+<https://huggingface.co/marcoyang/icefall-audio-tagging-audioset-zipformer-small-2024-04-23#/>
+
+The model achieves the following mean averaged precision on AudioSet:
+
+| Model | mAP |
+| ------ | ------- |
+| Zipformer-S-AT | 45.1 |
+
+The training command is:
+
+```bash
+export CUDA_VISIBLE_DEVICES="4,5,6,7"
+subset=full
+
+python zipformer/train.py \
+    --world-size 4 \
+    --num-epochs 50 \
+    --exp-dir zipformer/exp_small_at_as_${subset} \
+    --start-epoch 1 \
+    --use-fp16 1 \
+    --num-events 527 \
+    --num-encoder-layers 2,2,2,2,2,2 \
+    --feedforward-dim 512,768,768,768,768,768 \
+    --encoder-dim 192,256,256,256,256,256 \
+    --encoder-unmasked-dim 192,192,192,192,192,192 \
+    --audioset-subset $subset \
+    --max-duration 1200 \
+    --enable-musan True \
+    --master-port 13455
+```
+
+The evaluation command is:
+
+```bash
+python zipformer/evaluate.py \
+    --epoch 31 \
+    --avg 4 \
+    --num-encoder-layers 2,2,2,2,2,2 \
+    --feedforward-dim 512,768,768,768,768,768 \
+    --encoder-dim 192,256,256,256,256,256 \
+    --encoder-unmasked-dim 192,192,192,192,192,192 \
+    --exp-dir zipformer/exp_small_at_as_full \
+    --max-duration 500
+```