How do I train lstm on less data and not overfit?

So I have transcript of chats. Unfortunately there are 155 transcripts.
This is a classification problem with 14 classes.

I tried training a lstm, but the overall trend is overfitting. Even if I can get 60-70 percent accuracy, it will be more than enough.

The model's that I tried had an embedding layer, one lstm with 2 units, one dense layer with 10 units, Relu and followed by an output layer with 14 units and softmax.

Thanks in advance.

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