osanseviero commited on
Commit
d0fbae8
1 Parent(s): 62aef60
README.md ADDED
@@ -0,0 +1,103 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ language: "eng"
3
+ tags:
4
+ - wikihow
5
+ - t5-small
6
+ - pytorch
7
+ - lm-head
8
+ - seq2seq
9
+ - t5
10
+ - pipeline:summarization
11
+ - summarization
12
+ datasets:
13
+ - Wikihow
14
+ widget:
15
+ - text: "Lack of fluids can lead to dry mouth, which is a leading cause of bad breath. Water
16
+ can also dilute any chemicals in your mouth or gut that are causing bad breath., Studies show that
17
+ eating 6 ounces of yogurt a day reduces the level of odor-causing compounds in the mouth. In
18
+ particular, look for yogurt containing the active bacteria Streptococcus thermophilus or
19
+ Lactobacillus bulgaricus., The abrasive nature of fibrous fruits and vegetables helps to clean
20
+ teeth, while the vitamins, antioxidants, and acids they contain improve dental health.Foods that can
21
+ be particularly helpful include:Apples — Apples contain vitamin C, which is necessary for health
22
+ gums, as well as malic acid, which helps to whiten teeth.Carrots — Carrots are rich in vitamin A,
23
+ which strengthens tooth enamel.Celery — Chewing celery produces a lot of saliva, which helps to
24
+ neutralize bacteria that cause bad breath.Pineapples — Pineapples contain bromelain, an enzyme that
25
+ cleans the mouth., These teas have been shown to kill the bacteria that cause bad breath and
26
+ plaque., An upset stomach can lead to burping, which contributes to bad breath. Don’t eat foods that
27
+ upset your stomach, or if you do, use antacids. If you are lactose intolerant, try lactase tablets.,
28
+ They can all cause bad breath. If you do eat them, bring sugar-free gum or a toothbrush and
29
+ toothpaste to freshen your mouth afterwards., Diets low in carbohydrates lead to ketosis — a state
30
+ in which the body burns primarily fat instead of carbohydrates for energy. This may be good for your
31
+ waistline, but it also produces chemicals called ketones, which contribute to bad breath.To stop the
32
+ problem, you must change your diet. Or, you can combat the smell in one of these ways:Drink lots of
33
+ water to dilute the ketones.Chew sugarless gum or suck on sugarless mints.Chew mint leaves."
34
+ - text: " Bring 1/2 cup water to the boil.Add the fresh or dried rosemary to the water.Remove
35
+ from the heat. Set aside for 1/2 an hour to infuse. Added flavour can be released by pressing down
36
+ on the rosemary leaves with a spoon. Add the pieces to the blender or food processor with the
37
+ elderflower cordial. Blend or process to a purée.,, Add the lemon or lime juice and stir to
38
+ combine., Add a cover and place in the freezer.After 2 hours, remove from the freezer and break up
39
+ with a fork. This helps the ice crystals to form properly.Continue doing this every hour until the
40
+ granita freezes properly. Scoop the granita into dessert bowls and serve. Garnish with a cucumber
41
+ curl or a small sprig of rosemary."
42
+ metrics:
43
+ - Rouge1: 31.2
44
+ - RougeL: 24.5
45
+ ---
46
+
47
+ # Model name
48
+ Wikihow T5-small
49
+
50
+ ## Model description
51
+
52
+ This is a T5-small model trained on Wikihow All data set. The model was trained for 3 epochs using a batch size of 16 and learning rate of 3e-4. Max_input_lngth is set as 512 and max_output_length is 150. Model attained a Rouge1 score of 31.2 and RougeL score of 24.5.
53
+ We have written a blog post that covers the training procedure. Please find it [here](https://medium.com/@priya.dwivedi/fine-tuning-a-t5-transformer-for-any-summarization-task-82334c64c81).
54
+
55
+ ## Usage
56
+
57
+ ```
58
+ from transformers import AutoTokenizer, AutoModelWithLMHead
59
+
60
+ tokenizer = AutoTokenizer.from_pretrained("deep-learning-analytics/wikihow-t5-small")
61
+ model = AutoModelWithLMHead.from_pretrained("deep-learning-analytics/wikihow-t5-small")
62
+
63
+ device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
64
+ model = model.to(device)
65
+
66
+ text = """"
67
+ Lack of fluids can lead to dry mouth, which is a leading cause of bad breath. Water
68
+ can also dilute any chemicals in your mouth or gut that are causing bad breath., Studies show that
69
+ eating 6 ounces of yogurt a day reduces the level of odor-causing compounds in the mouth. In
70
+ particular, look for yogurt containing the active bacteria Streptococcus thermophilus or
71
+ Lactobacillus bulgaricus., The abrasive nature of fibrous fruits and vegetables helps to clean
72
+ teeth, while the vitamins, antioxidants, and acids they contain improve dental health.Foods that can
73
+ be particularly helpful include:Apples — Apples contain vitamin C, which is necessary for health
74
+ gums, as well as malic acid, which helps to whiten teeth.Carrots — Carrots are rich in vitamin A,
75
+ which strengthens tooth enamel.Celery — Chewing celery produces a lot of saliva, which helps to
76
+ neutralize bacteria that cause bad breath.Pineapples — Pineapples contain bromelain, an enzyme that
77
+ cleans the mouth., These teas have been shown to kill the bacteria that cause bad breath and
78
+ plaque., An upset stomach can lead to burping, which contributes to bad breath. Don’t eat foods that
79
+ upset your stomach, or if you do, use antacids. If you are lactose intolerant, try lactase tablets.,
80
+ They can all cause bad breath. If you do eat them, bring sugar-free gum or a toothbrush and
81
+ toothpaste to freshen your mouth afterwards., Diets low in carbohydrates lead to ketosis — a state
82
+ in which the body burns primarily fat instead of carbohydrates for energy. This may be good for your
83
+ waistline, but it also produces chemicals called ketones, which contribute to bad breath.To stop the
84
+ problem, you must change your diet. Or, you can combat the smell in one of these ways:Drink lots of
85
+ water to dilute the ketones.Chew sugarless gum or suck on sugarless mints.Chew mint leaves.
86
+ """
87
+
88
+ preprocess_text = text.strip().replace("\n","")
89
+ tokenized_text = tokenizer.encode(preprocess_text, return_tensors="pt").to(device)
90
+
91
+ summary_ids = model.generate(
92
+ tokenized_text,
93
+ max_length=150,
94
+ num_beams=2,
95
+ repetition_penalty=2.5,
96
+ length_penalty=1.0,
97
+ early_stopping=True
98
+ )
99
+
100
+ output = tokenizer.decode(summary_ids[0], skip_special_tokens=True)
101
+
102
+ print ("\n\nSummarized text: \n",output)
103
+ ```
config.json ADDED
@@ -0,0 +1,34 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "architectures": [
3
+ "T5ForConditionalGeneration"
4
+ ],
5
+ "d_ff": 2048,
6
+ "d_kv": 64,
7
+ "d_model": 512,
8
+ "decoder_start_token_id": 0,
9
+ "dropout_rate": 0.1,
10
+ "eos_token_id": 1,
11
+ "initializer_factor": 1.0,
12
+ "is_encoder_decoder": true,
13
+ "layer_norm_epsilon": 1e-06,
14
+ "model_type": "t5",
15
+ "n_positions": 512,
16
+ "num_heads": 8,
17
+ "num_layers": 6,
18
+ "output_past": true,
19
+ "pad_token_id": 0,
20
+ "relative_attention_num_buckets": 32,
21
+ "save_step": 0,
22
+ "task_specific_params": {
23
+ "summarization": {
24
+ "early_stopping": true,
25
+ "length_penalty": 2.0,
26
+ "max_length": 200,
27
+ "min_length": 30,
28
+ "no_repeat_ngram_size": 3,
29
+ "num_beams": 4,
30
+ "prefix": "summarize: "
31
+ }
32
+ },
33
+ "vocab_size": 32128
34
+ }
pytorch_model.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:9374d3f2ab7f758b7a00ea70b1ac2608aac13c67d37a7131987cc221b867dc23
3
+ size 242068027
special_tokens_map.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"eos_token": "</s>", "unk_token": "<unk>", "pad_token": "<pad>", "additional_special_tokens": ["<extra_id_0>", "<extra_id_1>", "<extra_id_2>", "<extra_id_3>", "<extra_id_4>", "<extra_id_5>", "<extra_id_6>", "<extra_id_7>", "<extra_id_8>", "<extra_id_9>", "<extra_id_10>", "<extra_id_11>", "<extra_id_12>", "<extra_id_13>", "<extra_id_14>", "<extra_id_15>", "<extra_id_16>", "<extra_id_17>", "<extra_id_18>", "<extra_id_19>", "<extra_id_20>", "<extra_id_21>", "<extra_id_22>", "<extra_id_23>", "<extra_id_24>", "<extra_id_25>", "<extra_id_26>", "<extra_id_27>", "<extra_id_28>", "<extra_id_29>", "<extra_id_30>", "<extra_id_31>", "<extra_id_32>", "<extra_id_33>", "<extra_id_34>", "<extra_id_35>", "<extra_id_36>", "<extra_id_37>", "<extra_id_38>", "<extra_id_39>", "<extra_id_40>", "<extra_id_41>", "<extra_id_42>", "<extra_id_43>", "<extra_id_44>", "<extra_id_45>", "<extra_id_46>", "<extra_id_47>", "<extra_id_48>", "<extra_id_49>", "<extra_id_50>", "<extra_id_51>", "<extra_id_52>", "<extra_id_53>", "<extra_id_54>", "<extra_id_55>", "<extra_id_56>", "<extra_id_57>", "<extra_id_58>", "<extra_id_59>", "<extra_id_60>", "<extra_id_61>", "<extra_id_62>", "<extra_id_63>", "<extra_id_64>", "<extra_id_65>", "<extra_id_66>", "<extra_id_67>", "<extra_id_68>", "<extra_id_69>", "<extra_id_70>", "<extra_id_71>", "<extra_id_72>", "<extra_id_73>", "<extra_id_74>", "<extra_id_75>", "<extra_id_76>", "<extra_id_77>", "<extra_id_78>", "<extra_id_79>", "<extra_id_80>", "<extra_id_81>", "<extra_id_82>", "<extra_id_83>", "<extra_id_84>", "<extra_id_85>", "<extra_id_86>", "<extra_id_87>", "<extra_id_88>", "<extra_id_89>", "<extra_id_90>", "<extra_id_91>", "<extra_id_92>", "<extra_id_93>", "<extra_id_94>", "<extra_id_95>", "<extra_id_96>", "<extra_id_97>", "<extra_id_98>", "<extra_id_99>"]}
spiece.model ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:d60acb128cf7b7f2536e8f38a5b18a05535c9e14c7a355904270e15b0945ea86
3
+ size 791656
tokenizer_config.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"model_max_length": 512}