Update README.md

README.md

@@ -71,8 +71,8 @@ To transfer knowledge from English model to Czech, we developed a simple method
 Figure 4: Test perplexity over the course of training for vocabulary swap (swapping 1.7K tokens) method on TinyLLAMA. Our method (green curve) vs TinyLLAMA training from scratch (blue curve).
 
 We also verify that finetuning from English to Czech is beneficial for MPT-7B model, compared from training a new model, at least on the first 10K steps. The training also seems to be more stable (notice yellow spike around 10k steps).
-Figure 5: Test cross-entropy over the course of training on CSMPT7B (yellow-red). Comparison with TinyLLAMA (blue-green). Our method (red&green curve) vs TinyLLAMA training from scratch (yellow&blue curve).
 <img src="figures/csmpt_tllama_test.png" width="900"/>
+Figure 5: Test cross-entropy over the course of training on CSMPT7B (yellow-red). Comparison with TinyLLAMA (blue-green). Our method (red&green curve) vs TinyLLAMA training from scratch (yellow&blue curve).
 
 The vocabulary swap was done the same way as our [Czech-GPT-2](https://huggingface.co/BUT-FIT/Czech-GPT-2-XL-133k) model (check it out for comprehensive description.)
 For CSMPT7b, we managed to align 4,177 english tokens with corresponding czech tokens.