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: 18.47
     - name: ROUGE-L (Question Generation)
       type: rouge_l_question_generation
-      value: 2.7
+      value: 33.98
     - name: METEOR (Question Generation)
       type: meteor_question_generation
-      value: 2.63
+      value: 28.96
     - name: BERTScore (Question Generation)
       type: bertscore_question_generation
-      value: 55.18
+      value: 86.62
     - name: MoverScore (Question Generation)
       type: moverscore_question_generation
-      value: 46.92
+      value: 65.33
 ---
 
 # Model Card of `vocabtrimmer/mt5-small-trimmed-ru-60000-ruquad-qg`
-This model is fine-tuned version of [vocabtrimmer/mt5-small-trimmed-ru-60000](https://huggingface.co/vocabtrimmer/mt5-small-trimmed-ru-60000) 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-60000](https://huggingface.co/ckpts/mt5-small-trimmed-ru-60000) 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-60000](https://huggingface.co/vocabtrimmer/mt5-small-trimmed-ru-60000)   
+- **Language model:** [ckpts/mt5-small-trimmed-ru-60000](https://huggingface.co/ckpts/mt5-small-trimmed-ru-60000)   
 - **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  |   55.18 | default | [lmqg/qg_ruquad](https://huggingface.co/datasets/lmqg/qg_ruquad) |
-| Bleu_1     |    2.83 | default | [lmqg/qg_ruquad](https://huggingface.co/datasets/lmqg/qg_ruquad) |
-| Bleu_2     |    0.24 | 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     |    2.63 | default | [lmqg/qg_ruquad](https://huggingface.co/datasets/lmqg/qg_ruquad) |
-| MoverScore |   46.92 | default | [lmqg/qg_ruquad](https://huggingface.co/datasets/lmqg/qg_ruquad) |
-| ROUGE_L    |    2.7  | default | [lmqg/qg_ruquad](https://huggingface.co/datasets/lmqg/qg_ruquad) |
+| BERTScore  |   86.62 | default | [lmqg/qg_ruquad](https://huggingface.co/datasets/lmqg/qg_ruquad) |
+| Bleu_1     |   34.5  | default | [lmqg/qg_ruquad](https://huggingface.co/datasets/lmqg/qg_ruquad) |
+| Bleu_2     |   27.55 | default | [lmqg/qg_ruquad](https://huggingface.co/datasets/lmqg/qg_ruquad) |
+| Bleu_3     |   22.43 | default | [lmqg/qg_ruquad](https://huggingface.co/datasets/lmqg/qg_ruquad) |
+| Bleu_4     |   18.47 | default | [lmqg/qg_ruquad](https://huggingface.co/datasets/lmqg/qg_ruquad) |
+| METEOR     |   28.96 | default | [lmqg/qg_ruquad](https://huggingface.co/datasets/lmqg/qg_ruquad) |
+| MoverScore |   65.33 | default | [lmqg/qg_ruquad](https://huggingface.co/datasets/lmqg/qg_ruquad) |
+| ROUGE_L    |   33.98 | default | [lmqg/qg_ruquad](https://huggingface.co/datasets/lmqg/qg_ruquad) |
 
 
 
@@ -108,10 +108,10 @@ The following hyperparameters were used during fine-tuning:
  - input_types: paragraph_answer
  - output_types: question
  - prefix_types: None
- - model: vocabtrimmer/mt5-small-trimmed-ru-60000
+ - model: ckpts/mt5-small-trimmed-ru-60000
  - max_length: 512
  - max_length_output: 32
- - epoch: 15
+ - epoch: 14
  - batch: 16
  - lr: 0.001
  - fp16: False

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

@@ -1 +1 @@
-{"validation": {"Bleu_1": 0.027557932263814127, "Bleu_2": 0.0027487162902328447, "Bleu_3": 5.475358703077925e-09, "Bleu_4": 7.954656170113785e-12}, "test": {"Bleu_1": 0.02817624765345468, "Bleu_2": 0.002340632956960454, "Bleu_3": 4.906083525994567e-09, "Bleu_4": 7.309588795172406e-12}}
+{"validation": {"Bleu_1": 0.3423540390311125, "Bleu_2": 0.2733429762088623, "Bleu_3": 0.22223874985383327, "Bleu_4": 0.1826195371841126}, "test": {"Bleu_1": 0.3427695781917828, "Bleu_2": 0.27370688801671383, "Bleu_3": 0.22283917977845238, "Bleu_4": 0.18341211794303808}}

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

@@ -1 +1 @@
-{"validation": {"Bleu_1": 0.027656952298100123, "Bleu_2": 0.002776886272190007, "Bleu_3": 5.544118885310694e-09, "Bleu_4": 8.064356058532987e-12, "METEOR": 0.026114412425185165, "ROUGE_L": 0.0268238493996731, "BERTScore": 0.552118055010524, "MoverScore": 0.4692170396594667}, "test": {"Bleu_1": 0.028323574841049817, "Bleu_2": 0.0023632756596974522, "Bleu_3": 4.960805698363e-09, "Bleu_4": 7.396491058460421e-12, "METEOR": 0.0263261088204675, "ROUGE_L": 0.026992587962960068, "BERTScore": 0.5518454402655153, "MoverScore": 0.4691894897887193}}
+{"validation": {"Bleu_1": 0.3437551491184639, "Bleu_2": 0.2743764724488608, "Bleu_3": 0.22302812361354818, "Bleu_4": 0.18332008281766346, "METEOR": 0.29110156552868266, "ROUGE_L": 0.34032719141701145, "BERTScore": 0.8664273309198426, "MoverScore": 0.6529300156189595}, "test": {"Bleu_1": 0.3449927341943072, "Bleu_2": 0.275515473791491, "Bleu_3": 0.224348981621882, "Bleu_4": 0.1846555124042022, "METEOR": 0.2896417180224368, "ROUGE_L": 0.33975145928375533, "BERTScore": 0.8661517296792998, "MoverScore": 0.653338765504722}}