| --- |
| license: other |
| base_model: facebook/bart-large-cnn |
| tags: |
| - generated_from_trainer |
| metrics: |
| - rouge |
| model-index: |
| - name: InstructTweetSummarizer |
| results: [] |
| language: |
| - en |
| pipeline_tag: summarization |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # InstructTweetSummarizer |
|
|
| This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co/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](https://huggingface.co/transformers/main_classes/pipelines.html): |
| |
| ```python |
| 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 |
