model update

README.md

@@ -14,7 +14,7 @@ pipeline_tag: text2text-generation
 tags:
 - questions and answers generation
 widget:
-- text: "Beyonce further expanded her acting career, starring as blues singer Etta James in the 2008 musical biopic, Cadillac Records."
+- text: " Beyonce further expanded her acting career, starring as blues singer Etta James in the 2008 musical biopic, Cadillac Records."
   example_title: "Questions & Answers Generation Example 1" 
 model-index:
 - name: lmqg/bart-large-tweetqa-qag
@@ -29,19 +29,19 @@ model-index:
     metrics:
     - name: BLEU4
       type: bleu4
-      value: 2.8048329690270435e-06
+      value: 0.15175643909660202
     - name: ROUGE-L
       type: rouge-l
-      value: 0.0054592489059451365
+      value: 0.34985377392591416
     - name: METEOR
       type: meteor
-      value: 0.003716401143099354
+      value: 0.2790788570524155
     - name: BERTScore
       type: bertscore
-      value: 0.0396099910543256
+      value: 0.9126712936479886
     - name: MoverScore
       type: moverscore
-      value: 0.45622891735080945
+      value: 0.62254961921224
 ---
 
 # Model Card of `lmqg/bart-large-tweetqa-qag`
@@ -94,7 +94,7 @@ from transformers import pipeline
 # initialize model
 pipe = pipeline("text2text-generation", 'lmqg/bart-large-tweetqa-qag')
 # question generation
-question = pipe('generate question and answer:  Beyonce further expanded her acting career, starring as blues singer Etta James in the 2008 musical biopic, Cadillac Records.')
+question = pipe(' Beyonce further expanded her acting career, starring as blues singer Etta James in the 2008 musical biopic, Cadillac Records.')
 
 ```
 
@@ -105,7 +105,7 @@ question = pipe('generate question and answer:  Beyonce further expanded her act
 
 | Dataset | Type | BLEU4 | ROUGE-L | METEOR | BERTScore | MoverScore | Link |
 |:--------|:-----|------:|--------:|-------:|----------:|-----------:|-----:|
-| [lmqg/qag_tweetqa](https://huggingface.co/datasets/lmqg/qag_tweetqa) | default | 0.0 | 0.005 | 0.004 | 0.04 | 0.456 | [link](https://huggingface.co/lmqg/bart-large-tweetqa-qag/raw/main/eval/metric.first.sentence.paragraph.questions_answers.lmqg_qag_tweetqa.default.json) | 
+| [lmqg/qag_tweetqa](https://huggingface.co/datasets/lmqg/qag_tweetqa) | default | 0.152 | 0.35 | 0.279 | 0.913 | 0.623 | [link](https://huggingface.co/lmqg/bart-large-tweetqa-qag/raw/main/eval/metric.first.answer.paragraph.questions_answers.lmqg_qag_tweetqa.default.json) | 
 
 
 
@@ -126,7 +126,7 @@ The following hyperparameters were used during fine-tuning:
  - lr: 5e-05
  - fp16: False
  - random_seed: 1
- - gradient_accumulation_steps: 4
+ - gradient_accumulation_steps: 8
  - label_smoothing: 0.15
 
 The full configuration can be found at [fine-tuning config file](https://huggingface.co/lmqg/bart-large-tweetqa-qag/raw/main/trainer_config.json).

config.json

@@ -1,5 +1,5 @@
 {
-  "_name_or_path": "lmqg_output/bart_large_tweetqa/best_model",
+  "_name_or_path": "lmqg_output/bart_large_tweetqa/model_xfrxcu/epoch_10",
   "activation_dropout": 0.1,
   "activation_function": "gelu",
   "add_bias_logits": false,

eval/metric.first.answer.paragraph.questions_answers.lmqg_qag_tweetqa.default.json

@@ -1 +1 @@
-{"validation": {"Bleu_1": 0.0002064254230651459, "Bleu_2": 4.486948524277899e-05, "Bleu_3": 1.5504808143022868e-05, "Bleu_4": 8.148462670214756e-06}, "test": {"Bleu_1": 7.040838585481249e-05, "Bleu_2": 1.1582844647284817e-05, "Bleu_3": 3.326224814299149e-06, "Bleu_4": 1.203121155394519e-06}}
+{"validation": {"Bleu_1": 0.43188759926692244, "Bleu_2": 0.30011779847872594, "Bleu_3": 0.20914603335217866, "Bleu_4": 0.14555259594468786, "METEOR": 0.3154636133794367, "ROUGE_L": 0.37165690881702945, "BERTScore": 0.9110018380919206, "MoverScore": 0.6290265297078133}, "test": {"Bleu_1": 0.44545454545451546, "Bleu_2": 0.3115127823844136, "Bleu_3": 0.21584316619841207, "Bleu_4": 0.15175643909660202, "METEOR": 0.2790788570524155, "ROUGE_L": 0.34985377392591416, "BERTScore": 0.9126712936479886, "MoverScore": 0.62254961921224}}

pytorch_model.bin

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:855c8b431a9bf3463503050051839b61bcd0770a89f9ee6d930a281fb7e5e17d
-size 1625534721
+oid sha256:2f9df6d58c40c56f82dc5319b30e6988f5050f7931c8b3528b42209acd0c50a4
+size 1625541889

tokenizer_config.json

@@ -6,7 +6,7 @@
   "errors": "replace",
   "mask_token": "<mask>",
   "model_max_length": 1024,
-  "name_or_path": "lmqg_output/bart_large_tweetqa/best_model",
+  "name_or_path": "lmqg_output/bart_large_tweetqa/model_xfrxcu/epoch_10",
   "pad_token": "<pad>",
   "sep_token": "</s>",
   "special_tokens_map_file": null,

trainer_config.json

@@ -1 +1 @@
-{"dataset_path": "lmqg/qag_tweetqa", "dataset_name": "default", "input_types": ["paragraph"], "output_types": ["questions_answers"], "prefix_types": null, "model": "facebook/bart-large", "max_length": 256, "max_length_output": 128, "epoch": 14, "batch": 32, "lr": 5e-05, "fp16": false, "random_seed": 1, "gradient_accumulation_steps": 4, "label_smoothing": 0.15}
+{"dataset_path": "lmqg/qag_tweetqa", "dataset_name": "default", "input_types": ["paragraph"], "output_types": ["questions_answers"], "prefix_types": null, "model": "facebook/bart-large", "max_length": 256, "max_length_output": 128, "epoch": 14, "batch": 32, "lr": 5e-05, "fp16": false, "random_seed": 1, "gradient_accumulation_steps": 8, "label_smoothing": 0.15}