InstructTweetSummarizer
This model is a fine-tuned version of facebook/bart-large-cnn on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3548
- Rouge1: 47.5134
- Rouge2: 24.7121
- Rougel: 35.7366
- Rougelsum: 35.6499
- Gen Len: 111.96
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 6
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 12
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
Training Loss |
Epoch |
Step |
Validation Loss |
Rouge1 |
Rouge2 |
Rougel |
Rougelsum |
Gen Len |
No log |
1.0 |
417 |
0.3468 |
44.9326 |
22.3736 |
33.008 |
32.9247 |
116.43 |
0.5244 |
2.0 |
834 |
0.3440 |
46.9139 |
24.683 |
35.3699 |
35.333 |
119.65 |
0.2061 |
3.0 |
1251 |
0.3548 |
47.5134 |
24.7121 |
35.7366 |
35.6499 |
111.96 |
How to use
Here is how to use this model with the pipeline API:
from transformers import pipeline
summarizer = pipeline("summarization", model="Sidharthkr/InstructTweetSummarizer")
def summarymaker(instruction = "", tweets = ""):
ARTICLE = f"""[INST] {instruction} [/INST] \\n [TWEETS] {tweets} [/TWEETS]"""
out = summarizer(ARTICLE, max_length=130, min_length=10, do_sample=False)
out = out[0]['summary_text'].split("[SUMMARY]")[-1].split("[/")[0].split("[via")[0].strip()
return out
summarymaker(instruction = "Summarize the tweets for Stellantis in 100 words",
tweets = """Stellantis - arch critic of Chinese EVs coming to Europe - is in talks with CATL to build a European plant. \n\nIt has concluded that cutting the price of EVs by using Chinese LFP batteries is more important.\n\n@FT story: \nhttps://t.co/l7nGggRFxH. State-of-the-art North America Battery Technology Centre begins to take shape at Stellantis' Automotive Research and Development Centre (ARDC) in Windsor, Ontario.\n\nhttps://t.co/04RO7CL1O5. RT @UAW: 🧵After the historic Stand Up Strike, UAW members at Ford, General Motors and Stellantis have voted to ratify their new contracts,…. RT @atorsoli: Stellantis and CATL are set to supply lower-cost EV batteries together for Europe, signaling automaker's efforts to tighten t…. RT @atorsoli: Stellantis and CATL are set to supply lower-cost EV batteries together for Europe, signaling automaker's efforts to tighten""")
>>> 'Stellantis is in talks with CATL to build a European plant, with a focus on cutting the price of EVs by using Chinese LFP batteries. The company is also developing a state-of-the-art North America Battery Technology Centre in Windsor, Ontario, and has ratified its new contracts with the UAW.'
Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0
- Datasets 2.14.7
- Tokenizers 0.14.1