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: 7.39
     - name: ROUGE-L (Question Generation)
       type: rouge_l_question_generation
-      value: 0.46
+      value: 21.97
     - name: METEOR (Question Generation)
       type: meteor_question_generation
-      value: 0.37
+      value: 17.97
     - name: BERTScore (Question Generation)
       type: bertscore_question_generation
-      value: 56.13
+      value: 80.84
     - name: MoverScore (Question Generation)
       type: moverscore_question_generation
-      value: 45.75
+      value: 56.84
 ---
 
 # Model Card of `vocabtrimmer/mt5-small-trimmed-it-15000-itquad-qg`
-This model is fine-tuned version of [vocabtrimmer/mt5-small-trimmed-it-15000](https://huggingface.co/vocabtrimmer/mt5-small-trimmed-it-15000) for question generation task on the [lmqg/qg_itquad](https://huggingface.co/datasets/lmqg/qg_itquad) (dataset_name: default) via [`lmqg`](https://github.com/asahi417/lm-question-generation).
+This model is fine-tuned version of [ckpts/mt5-small-trimmed-it-15000](https://huggingface.co/ckpts/mt5-small-trimmed-it-15000) for question generation task on the [lmqg/qg_itquad](https://huggingface.co/datasets/lmqg/qg_itquad) (dataset_name: default) via [`lmqg`](https://github.com/asahi417/lm-question-generation).
 
 
 ### Overview
-- **Language model:** [vocabtrimmer/mt5-small-trimmed-it-15000](https://huggingface.co/vocabtrimmer/mt5-small-trimmed-it-15000)   
+- **Language model:** [ckpts/mt5-small-trimmed-it-15000](https://huggingface.co/ckpts/mt5-small-trimmed-it-15000)   
 - **Language:** it  
 - **Training data:** [lmqg/qg_itquad](https://huggingface.co/datasets/lmqg/qg_itquad) (default)
 - **Online Demo:** [https://autoqg.net/](https://autoqg.net/)
@@ -89,14 +89,14 @@ output = pipe("<hl> Dopo il 1971 <hl> , l' OPEC ha tardato ad adeguare i prezzi
 
 |            |   Score | Type    | Dataset                                                          |
 |:-----------|--------:|:--------|:-----------------------------------------------------------------|
-| BERTScore  |   56.13 | default | [lmqg/qg_itquad](https://huggingface.co/datasets/lmqg/qg_itquad) |
-| Bleu_1     |    0.49 | default | [lmqg/qg_itquad](https://huggingface.co/datasets/lmqg/qg_itquad) |
-| Bleu_2     |    0    | default | [lmqg/qg_itquad](https://huggingface.co/datasets/lmqg/qg_itquad) |
-| Bleu_3     |    0    | default | [lmqg/qg_itquad](https://huggingface.co/datasets/lmqg/qg_itquad) |
-| Bleu_4     |    0    | default | [lmqg/qg_itquad](https://huggingface.co/datasets/lmqg/qg_itquad) |
-| METEOR     |    0.37 | default | [lmqg/qg_itquad](https://huggingface.co/datasets/lmqg/qg_itquad) |
-| MoverScore |   45.75 | default | [lmqg/qg_itquad](https://huggingface.co/datasets/lmqg/qg_itquad) |
-| ROUGE_L    |    0.46 | default | [lmqg/qg_itquad](https://huggingface.co/datasets/lmqg/qg_itquad) |
+| BERTScore  |   80.84 | default | [lmqg/qg_itquad](https://huggingface.co/datasets/lmqg/qg_itquad) |
+| Bleu_1     |   22.63 | default | [lmqg/qg_itquad](https://huggingface.co/datasets/lmqg/qg_itquad) |
+| Bleu_2     |   14.89 | default | [lmqg/qg_itquad](https://huggingface.co/datasets/lmqg/qg_itquad) |
+| Bleu_3     |   10.35 | default | [lmqg/qg_itquad](https://huggingface.co/datasets/lmqg/qg_itquad) |
+| Bleu_4     |    7.39 | default | [lmqg/qg_itquad](https://huggingface.co/datasets/lmqg/qg_itquad) |
+| METEOR     |   17.97 | default | [lmqg/qg_itquad](https://huggingface.co/datasets/lmqg/qg_itquad) |
+| MoverScore |   56.84 | default | [lmqg/qg_itquad](https://huggingface.co/datasets/lmqg/qg_itquad) |
+| ROUGE_L    |   21.97 | default | [lmqg/qg_itquad](https://huggingface.co/datasets/lmqg/qg_itquad) |
 
 
 
@@ -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-it-15000
+ - model: ckpts/mt5-small-trimmed-it-15000
  - max_length: 512
  - max_length_output: 32
- - epoch: 5
+ - 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_itquad.default.json

@@ -1 +1 @@
-{"validation": {"Bleu_1": 0.004567010551539636, "Bleu_2": 7.839137355436766e-12, "Bleu_3": 9.782026035497752e-15, "Bleu_4": 3.579750541003946e-16}, "test": {"Bleu_1": 0.004522989430174668, "Bleu_2": 7.723312821853149e-12, "Bleu_3": 9.62131954572275e-15, "Bleu_4": 3.518167352053418e-16}}
+{"validation": {"Bleu_1": 0.2237564812373646, "Bleu_2": 0.14753299950187648, "Bleu_3": 0.10280911146604187, "Bleu_4": 0.07377165022174957}, "test": {"Bleu_1": 0.21637282038578534, "Bleu_2": 0.14133164217029193, "Bleu_3": 0.09786654734350055, "Bleu_4": 0.06969957830640872}}

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

@@ -1 +1 @@
-{"validation": {"Bleu_1": 0.0046197154338936145, "Bleu_2": 7.940249897814446e-12, "Bleu_3": 9.912802285169916e-15, "Bleu_4": 3.6285094356569344e-16, "METEOR": 0.0033732694546279363, "ROUGE_L": 0.0043499135820432395, "BERTScore": 0.5613967677697813, "MoverScore": 0.4577550994954912}, "test": {"Bleu_1": 0.004860953588974441, "Bleu_2": 8.433995825221792e-12, "Bleu_3": 1.0563157088977527e-14, "Bleu_4": 3.8730904015401617e-16, "METEOR": 0.00367127674240513, "ROUGE_L": 0.004590781821751085, "BERTScore": 0.561251641597745, "MoverScore": 0.4574736142731061}}
+{"validation": {"Bleu_1": 0.2247477276014349, "Bleu_2": 0.14836169499852286, "Bleu_3": 0.10348632514370129, "Bleu_4": 0.07432240696181995, "METEOR": 0.18438518959925088, "ROUGE_L": 0.22044772480710642, "BERTScore": 0.8135221853181978, "MoverScore": 0.5731971716488695}, "test": {"Bleu_1": 0.2263010379800928, "Bleu_2": 0.14893781520324303, "Bleu_3": 0.1035047817498138, "Bleu_4": 0.07385948007263937, "METEOR": 0.17973493970970986, "ROUGE_L": 0.21971071493386257, "BERTScore": 0.808444913420041, "MoverScore": 0.5683878416606393}}