commit files to HF hub

README.md

@@ -33,27 +33,27 @@ model-index:
     metrics:
     - name: BLEU4 (Question Generation)
       type: bleu4_question_generation
-      value: 0.0
+      value: 18.44
     - name: ROUGE-L (Question Generation)
       type: rouge_l_question_generation
-      value: 1.0
+      value: 33.96
     - name: METEOR (Question Generation)
       type: meteor_question_generation
-      value: 1.6
+      value: 29.21
     - name: BERTScore (Question Generation)
       type: bertscore_question_generation
-      value: 54.59
+      value: 86.35
     - name: MoverScore (Question Generation)
       type: moverscore_question_generation
-      value: 46.64
+      value: 65.04
 ---
 
 # Model Card of `vocabtrimmer/mt5-small-trimmed-ru-30000-ruquad-qg`
-This model is fine-tuned version of [vocabtrimmer/mt5-small-trimmed-ru-30000](https://huggingface.co/vocabtrimmer/mt5-small-trimmed-ru-30000) for question generation task on the [lmqg/qg_ruquad](https://huggingface.co/datasets/lmqg/qg_ruquad) (dataset_name: default) via [`lmqg`](https://github.com/asahi417/lm-question-generation).
+This model is fine-tuned version of [ckpts/mt5-small-trimmed-ru-30000](https://huggingface.co/ckpts/mt5-small-trimmed-ru-30000) for question generation task on the [lmqg/qg_ruquad](https://huggingface.co/datasets/lmqg/qg_ruquad) (dataset_name: default) via [`lmqg`](https://github.com/asahi417/lm-question-generation).
 
 
 ### Overview
-- **Language model:** [vocabtrimmer/mt5-small-trimmed-ru-30000](https://huggingface.co/vocabtrimmer/mt5-small-trimmed-ru-30000)   
+- **Language model:** [ckpts/mt5-small-trimmed-ru-30000](https://huggingface.co/ckpts/mt5-small-trimmed-ru-30000)   
 - **Language:** ru  
 - **Training data:** [lmqg/qg_ruquad](https://huggingface.co/datasets/lmqg/qg_ruquad) (default)
 - **Online Demo:** [https://autoqg.net/](https://autoqg.net/)
@@ -89,14 +89,14 @@ output = pipe("Нелишним будет отметить, что, разви
 
 |            |   Score | Type    | Dataset                                                          |
 |:-----------|--------:|:--------|:-----------------------------------------------------------------|
-| BERTScore  |   54.59 | default | [lmqg/qg_ruquad](https://huggingface.co/datasets/lmqg/qg_ruquad) |
-| Bleu_1     |    0.94 | default | [lmqg/qg_ruquad](https://huggingface.co/datasets/lmqg/qg_ruquad) |
-| Bleu_2     |    0    | default | [lmqg/qg_ruquad](https://huggingface.co/datasets/lmqg/qg_ruquad) |
-| Bleu_3     |    0    | default | [lmqg/qg_ruquad](https://huggingface.co/datasets/lmqg/qg_ruquad) |
-| Bleu_4     |    0    | default | [lmqg/qg_ruquad](https://huggingface.co/datasets/lmqg/qg_ruquad) |
-| METEOR     |    1.6  | default | [lmqg/qg_ruquad](https://huggingface.co/datasets/lmqg/qg_ruquad) |
-| MoverScore |   46.64 | default | [lmqg/qg_ruquad](https://huggingface.co/datasets/lmqg/qg_ruquad) |
-| ROUGE_L    |    1    | default | [lmqg/qg_ruquad](https://huggingface.co/datasets/lmqg/qg_ruquad) |
+| BERTScore  |   86.35 | default | [lmqg/qg_ruquad](https://huggingface.co/datasets/lmqg/qg_ruquad) |
+| Bleu_1     |   34.2  | default | [lmqg/qg_ruquad](https://huggingface.co/datasets/lmqg/qg_ruquad) |
+| Bleu_2     |   27.36 | default | [lmqg/qg_ruquad](https://huggingface.co/datasets/lmqg/qg_ruquad) |
+| Bleu_3     |   22.33 | default | [lmqg/qg_ruquad](https://huggingface.co/datasets/lmqg/qg_ruquad) |
+| Bleu_4     |   18.44 | default | [lmqg/qg_ruquad](https://huggingface.co/datasets/lmqg/qg_ruquad) |
+| METEOR     |   29.21 | default | [lmqg/qg_ruquad](https://huggingface.co/datasets/lmqg/qg_ruquad) |
+| MoverScore |   65.04 | default | [lmqg/qg_ruquad](https://huggingface.co/datasets/lmqg/qg_ruquad) |
+| ROUGE_L    |   33.96 | default | [lmqg/qg_ruquad](https://huggingface.co/datasets/lmqg/qg_ruquad) |
 
 
 
@@ -108,12 +108,12 @@ The following hyperparameters were used during fine-tuning:
  - input_types: paragraph_answer
  - output_types: question
  - prefix_types: None
- - model: vocabtrimmer/mt5-small-trimmed-ru-30000
+ - model: ckpts/mt5-small-trimmed-ru-30000
  - max_length: 512
  - max_length_output: 32
- - epoch: 17
+ - epoch: 13
  - batch: 16
- - lr: 0.0005
+ - lr: 0.001
  - fp16: False
  - random_seed: 1
  - gradient_accumulation_steps: 4

eval/metric.first.answer.paragraph_answer.question.lmqg_qg_ruquad.default.json

@@ -1 +1 @@
-{"validation": {"Bleu_1": 0.009799196787148438, "Bleu_2": 0.0005852737978964647, "Bleu_3": 1.872450066297381e-09, "Bleu_4": 3.4351742662096258e-12}, "test": {"Bleu_1": 0.009271586917116997, "Bleu_2": 1.2719814522167759e-11, "Bleu_3": 1.4573788253750512e-14, "Bleu_4": 5.059486786015269e-16}}
+{"validation": {"Bleu_1": 0.3363966955215555, "Bleu_2": 0.2685513229212724, "Bleu_3": 0.21805385924412107, "Bleu_4": 0.17879331823675573}, "test": {"Bleu_1": 0.3402116714952928, "Bleu_2": 0.27223546029454754, "Bleu_3": 0.22215274979551314, "Bleu_4": 0.18342740166657898}}

eval/metric.first.sentence.paragraph_answer.question.lmqg_qg_ruquad.default.json

@@ -1 +1 @@
-{"validation": {"Bleu_1": 0.00984820074676738, "Bleu_2": 0.0005911220113366271, "Bleu_3": 1.8943038111384596e-09, "Bleu_4": 3.4781834393905875e-12, "METEOR": 0.016419043854511567, "ROUGE_L": 0.010682781811433693, "BERTScore": 0.5459694829158621, "MoverScore": 0.4663293462842938}, "test": {"Bleu_1": 0.00937225422239563, "Bleu_2": 1.2880262413169668e-11, "Bleu_3": 1.4766198831191623e-14, "Bleu_4": 5.127782990981187e-16, "METEOR": 0.01595506138034452, "ROUGE_L": 0.009991331725971244, "BERTScore": 0.5458722341336752, "MoverScore": 0.4663653540034606}}
+{"validation": {"Bleu_1": 0.33797951395861947, "Bleu_2": 0.26973605882492135, "Bleu_3": 0.2189382598511983, "Bleu_4": 0.17950680759167334, "METEOR": 0.29138918909137734, "ROUGE_L": 0.3394018581752814, "BERTScore": 0.8635220512996968, "MoverScore": 0.6509559853998595}, "test": {"Bleu_1": 0.34198476335205574, "Bleu_2": 0.27362625179438677, "Bleu_3": 0.22330512922189116, "Bleu_4": 0.18435824142429255, "METEOR": 0.29214592246635307, "ROUGE_L": 0.33959203064606674, "BERTScore": 0.8634884899956702, "MoverScore": 0.650355332058682}}