update model card README.md

README.md

@@ -1,23 +1,82 @@
 ---
-language: 
-  - en
-tags:
-- transformers
 license: apache-2.0
-datasets:
-- dvitel/hearthstone
+tags:
+- generated_from_trainer
 metrics:
-- exact_match
 - bleu
-- dvitel/codebleu
-- chrf
+model-index:
+- name: h0
+  results: []
 ---
 
-Application of distilgpt2 to HearthStone card code synthesis. Dataset [dvitel/hearthstone](https://huggingface.co/datasets/dvitel/hearthstone) \
-Article under consideration: [Abstract Syntax Networks for Code Generation and Semantic Parsing](https://aclanthology.org/P17-1105.pdf) \
-We check if distilgpt2 could produce better results than ASNs from article. H0 model has minimal preprocessing of dataset where we normalize python code:
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# h0
+
+This model is a fine-tuned version of [distilgpt2](https://huggingface.co/distilgpt2) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3117
+- Exact Match: 0.1970
+- Bleu: 0.9085
+- Codebleu: 0.7341
+- Ngram Match Score: 0.7211
+- Weighted Ngram Match Score: 0.7299
+- Syntax Match Score: 0.7536
+- Dataflow Match Score: 0.7317
+- Chrf: 92.8689
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 2e-05
+- train_batch_size: 4
+- eval_batch_size: 4
+- seed: 17
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- num_epochs: 200
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch  | Step  | Validation Loss | Exact Match | Bleu   | Codebleu | Ngram Match Score | Weighted Ngram Match Score | Syntax Match Score | Dataflow Match Score | Chrf    |
+|:-------------:|:------:|:-----:|:---------------:|:-----------:|:------:|:--------:|:-----------------:|:--------------------------:|:------------------:|:--------------------:|:-------:|
+| 0.543         | 11.94  | 1600  | 0.2701          | 0.0152      | 0.8552 | 0.6144   | 0.6027            | 0.6136                     | 0.6431             | 0.5982               | 89.0280 |
+| 0.1459        | 23.88  | 3200  | 0.2408          | 0.0909      | 0.8841 | 0.6733   | 0.6610            | 0.6719                     | 0.7210             | 0.6393               | 91.2517 |
+| 0.0801        | 35.82  | 4800  | 0.2498          | 0.1515      | 0.8966 | 0.6999   | 0.6954            | 0.7054                     | 0.7326             | 0.6662               | 92.1356 |
+| 0.0498        | 47.76  | 6400  | 0.2569          | 0.1818      | 0.9012 | 0.7015   | 0.7022            | 0.7114                     | 0.7428             | 0.6496               | 92.4668 |
+| 0.0323        | 59.7   | 8000  | 0.2732          | 0.1667      | 0.9044 | 0.7241   | 0.7025            | 0.7123                     | 0.7551             | 0.7266               | 92.5429 |
+| 0.0214        | 71.64  | 9600  | 0.2896          | 0.1667      | 0.9034 | 0.7228   | 0.7101            | 0.7195                     | 0.7670             | 0.6945               | 92.4258 |
+| 0.015         | 83.58  | 11200 | 0.2870          | 0.1667      | 0.9046 | 0.7292   | 0.7137            | 0.7228                     | 0.7667             | 0.7137               | 92.5979 |
+| 0.0121        | 95.52  | 12800 | 0.2907          | 0.1667      | 0.9075 | 0.7287   | 0.7198            | 0.7297                     | 0.7696             | 0.6958               | 92.7074 |
+| 0.0093        | 107.46 | 14400 | 0.2976          | 0.1667      | 0.9073 | 0.7365   | 0.7134            | 0.7238                     | 0.7732             | 0.7356               | 92.8347 |
+| 0.0073        | 119.4  | 16000 | 0.3037          | 0.1818      | 0.9085 | 0.7326   | 0.7154            | 0.7241                     | 0.7529             | 0.7381               | 92.8343 |
+| 0.006         | 131.34 | 17600 | 0.3047          | 0.1970      | 0.9104 | 0.7410   | 0.7230            | 0.7312                     | 0.7667             | 0.7433               | 92.8286 |
+| 0.005         | 143.28 | 19200 | 0.3080          | 0.1970      | 0.9088 | 0.7377   | 0.7232            | 0.7316                     | 0.7746             | 0.7214               | 92.8035 |
+| 0.0044        | 155.22 | 20800 | 0.3071          | 0.1970      | 0.9076 | 0.7343   | 0.7196            | 0.7283                     | 0.7783             | 0.7112               | 92.7742 |
+| 0.004         | 167.16 | 22400 | 0.3097          | 0.1970      | 0.9082 | 0.7440   | 0.7236            | 0.7334                     | 0.7601             | 0.7587               | 92.8117 |
+| 0.0035        | 179.1  | 24000 | 0.3111          | 0.1970      | 0.9080 | 0.7355   | 0.7204            | 0.7295                     | 0.7616             | 0.7304               | 92.7990 |
+| 0.0036        | 191.04 | 25600 | 0.3117          | 0.1970      | 0.9085 | 0.7341   | 0.7211            | 0.7299                     | 0.7536             | 0.7317               | 92.8689 |
+
+
+### Framework versions
 
-```python
-def normalize(line:str):
-    return line.strip().replace("§", "\n").replace("    ", "\t").replace("\\ ", "").replace("\n\n", "\n")
-```
+- Transformers 4.24.0
+- Pytorch 1.13.0
+- Datasets 2.6.1
+- Tokenizers 0.13.1