Update README.md

README.md

@@ -9,6 +9,11 @@ metrics:
 model-index:
 - name: pos-polish-gpt2-large
   results: []
+license: mit
+datasets:
+- clarin-pl/nkjp-pos
+language:
+- pl
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -16,7 +21,7 @@ should probably proofread and complete it, then remove this comment. -->
 
 # pos-polish-gpt2-large
 
-This model was trained from scratch on an unknown dataset.
+This model was trained from [polish-gpt2-large](https://huggingface.co/sdadas/polish-gpt2-large) on [clarin-pl/nkjp-pos](https://huggingface.co/datasets/clarin-pl/nkjp-pos) dataset.
 It achieves the following results on the evaluation set:
 - Loss: 0.2290
 - Precision: 0.8910
@@ -26,18 +31,29 @@ It achieves the following results on the evaluation set:
 
 ## Model description
 
-More information needed
+Trained from [polish-gpt2-large](https://huggingface.co/sdadas/polish-gpt2-large)
 
 ## Intended uses & limitations
 
-More information needed
+Part-of-speech tagging for Polish language.
+Tags description at the bottom of http://nkjp.pl/poliqarp/help/plse2.html
 
 ## Training and evaluation data
 
-More information needed
+Dataset: [clarin-pl/nkjp-pos](https://huggingface.co/datasets/clarin-pl/nkjp-pos)
+
+Datacollator:
+```py
+from transformers import DataCollatorForTokenClassification
+data_collator = DataCollatorForTokenClassification(tokenizer=tokenizer)
+```
 
 ## Training procedure
 
+GPU: RTX 3090
+
+Training time: 01:15:31
+
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
@@ -56,6 +72,7 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+|               | 0.0   |    0 | 3.8487          | 3.8487    | 3.8487 | 3.8487 | 3.8487   |
 | 0.1952        | 1.0   | 2444 | 0.1942          | 0.8865    | 0.9304 | 0.9079 | 0.9426   |
 | 0.1287        | 2.0   | 4889 | 0.1984          | 0.8903    | 0.9322 | 0.9108 | 0.9449   |
 | 0.0832        | 3.0   | 7332 | 0.2290          | 0.8910    | 0.9328 | 0.9114 | 0.9450   |
@@ -66,4 +83,4 @@ The following hyperparameters were used during training:
 - Transformers 4.36.2
 - Pytorch 2.1.2+cu121
 - Datasets 2.16.1
-- Tokenizers 0.15.0
+- Tokenizers 0.15.0