Update README.md in accordance with the latest model push.

README.md

@@ -24,10 +24,11 @@ Moi!
 
 I used sentence pairs from https://tatoeba.org/ to finetune an NLLB model for Gronings. Consider this an early beta version!
 
-I am a linguist and speaker of Gronings so I carried out evaluation by expert's eyeball. The github repo contains some BLEU and ChrF score plots, but I haven't thoroughly investigated the performance by means of them and am hesitant to claim any particular general translation performance for this version.
-The model produces something that is recognizable as Gronings when the input language is Dutch. I found that interesting enough for a PoC, so I decided to publish.
-
-The model is not optimal in terms of hyperparameters, so I am planning to upload an even better version in the future.
+The github repo contains some BLEU and ChrF score plots, but I haven't thoroughly investigated the performance by means of them and am hesitant to claim any particular general translation performance for this version.
+Fortunately, I am a linguist and speaker of Gronings so I could carry out evaluation by expert's eyeball.
+The model generally produces acceptable Gronings when the input language is Dutch and the language is basic.
+I consider this interesting enough for a public PoC, so I decided to publish.
+It is certainly possible to create a better model by means of (synthetic) data addition and hyperparameter optimization. I have not employed backtranslation either yet.
 
 Update 10 September 2025: I've updated the code to the latest version of `transformers` so that it can immediately be used by anyone without any tokenizer black magic needed. Also about 500 more parallel nld-gos sentences were added to the training data.
 Only the additional Gronings language token needs to be added to the tokenizer at initialization, then everything should work.
@@ -36,6 +37,12 @@ Update 21 November 2025: I added another ~450 sentences and shortened training a
 
 Update 28 November 2025: Add another ~90 sentences. Upon further inspection, and inspired by https://www.youtube.com/watch?v=z64a7USuGX0 I decided to train for much longer, and this version seems to perform quite a bit better than the previous.
 
+Update 16 January 2026: Add a few hundred more sentences and allow longer sentences in training loop (at the cost of longer training time).
+
+See https://github.com/tom9358/nllb-tryout for everything (code, more documentation and references) except the model itself and training data.
+
+Check out the dedicated Huggingface space to try out the model! Find it here: https://huggingface.co/spaces/Tom9358/gos_gronings_translate
+
 <details>
   <summary>See here a minimal example code snippet to get the model up and running: (click)</summary>
 
@@ -56,12 +63,12 @@ def translate(text, src_lang: str = "nld_Latn", tgt_lang: str = "gos_Latn", **kw
         return_tensors='pt',
         padding='longest',
         truncation=True,
-        max_length=120
+        max_length=500
     )
     result = model.generate(
         **inputs.to(model.device),
         forced_bos_token_id=tokenizer.convert_tokens_to_ids(tgt_lang),
-        max_new_tokens=int(16 + 1.5 * inputs.input_ids.shape[1]),
+        max_new_tokens=int(20 + 1.6 * inputs.input_ids.shape[1]),
         **kwargs
     )
     return tokenizer.batch_decode(result, skip_special_tokens=True)
@@ -70,11 +77,7 @@ translate("Dit is een testzin om te kijken of de code werkt.")
 ```
 </details>
 
-See https://github.com/tom9358/nllb-tryout for everything (code, more documentation and references) except the model itself and training data.
-
-Check out the dedicated Huggingface space to try out the model!
-
-Alternatively, another (rather slow, but also free and accessible to everyone) way to try out the model:
+In case for some reason the HF space stops working, here is another (albeit slower) way to try out the model:
 https://colab.research.google.com/drive/1b5dn3VT4fvOBKly1CIx4Qwo59GDM1H-M
 
 The code there is also a minimal example of how to use this model.