Update README.md

README.md

@@ -35,7 +35,7 @@ There are three versions:
 ### Training Details
 
 1) Training Epochs are calculated from the number of full iterations of all dataset and were set from the n_step parameter in the initialization of Trainer.
-Finally, there are 1 for nano model, 1 for mini model, 10 for small model.
+Finally, there are 1 for nano model, 1 for mini model, 6 for small model.
 
 2) Batch Size: 32 - for nano and mini. 64 - for small.
 
@@ -92,8 +92,6 @@ Loss:
 
 ![image/png](https://cdn-uploads.huggingface.co/production/uploads/67c40beb3a3d19149b5bdfbf/tylbErxZYhKUOgv-YfNjH.png)
 
-Here is the neatly formatted Markdown table in English:
-
 Epoch:
 
 | Parameter | Min   | Max   | Cur   |
@@ -117,8 +115,8 @@ in the `small` - `small`:
 
 ```python
 # Small model
-model_small = TransformerForCausalLM.from_pretrained("estnafinema0/llm-course-hw1", revision="small")
-tokenizer = ByteLevelBPETokenizer.from_pretrained("estnafinema0/llm-course-hw1")
+model_small = TransformerForCausalLM.from_pretrained("estnafinema0/russian-jokes-generator ", revision="small")
+tokenizer = ByteLevelBPETokenizer.from_pretrained("estnafinema0/russian-jokes-generator ")
 ```
 
 To generate the examples with the initial prompt: