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--- |
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library_name: peft |
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base_model: google/flan-t5-base |
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--- |
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# Model Card for Model ID |
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This is a flan-t5-base model finetuned using QLoRA (PEFT) |
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on dialogSum dataset : https://huggingface.co/datasets/knkarthick/dialogsum |
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## Model Details |
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### Training Details: |
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This is just a basic fine tuned model using below training args and params |
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lora_config = LoraConfig( |
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r=16, |
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lora_alpha=32, |
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target_modules=['q','k','v','o'], |
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lora_dropout=.05, |
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bias='none', |
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task_type=TaskType.SEQ_2_SEQ_LM #flan-t5 |
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) |
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output_dir = f'/kaggle/working/qlora-peft-flant5-base-dialogue-summary-training-{str(int(time.time()))}' |
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peft_training_args_4bit = TrainingArguments( |
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output_dir=output_dir, |
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auto_find_batch_size=True, |
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learning_rate=1e-3, # Higher learning rate than full fine-tuning. |
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num_train_epochs=200, |
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logging_steps=10, |
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max_steps=200 |
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) |
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peft_trainer_4bit = Trainer( |
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model=peft_model_4bit, |
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args=peft_training_args_4bit, |
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train_dataset=tokenized_dataset_cleaned["train"], |
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eval_dataset=tokenized_dataset_cleaned['validation'] |
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) |
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Recorded training loss as below: |
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Step Training Loss |
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10 29.131100 |
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20 4.856900 |
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30 3.241400 |
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40 1.346500 |
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50 0.560900 |
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60 0.344000 |
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70 0.258600 |
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80 0.201600 |
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90 0.202900 |
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100 0.198700 |
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110 0.185000 |
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120 0.177200 |
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130 0.161400 |
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140 0.164200 |
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150 0.164300 |
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160 0.165800 |
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170 0.168700 |
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180 0.155100 |
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190 0.161200 |
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200 0.170300 |
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Rouge1 score for 100 test dataset(out of 1500) is : |
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ORIGINAL MODEL: |
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{'rouge1': 0.2232663790087573, 'rouge2': 0.06084131871447254, 'rougeL': 0.1936115999187245, 'rougeLsum': 0.19319411133637282} |
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PEFT MODEL: |
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{'rouge1': 0.34502805897556865, 'rouge2': 0.11517693222074701, 'rougeL': 0.2800665095598698, 'rougeLsum': 0.27941257109947587} |
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## Uses |
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<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> |
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### Direct Use |
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<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> |
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[More Information Needed] |
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### Downstream Use [optional] |
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<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> |
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[More Information Needed] |
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### Out-of-Scope Use |
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<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> |
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[More Information Needed] |
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## Bias, Risks, and Limitations |
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<!-- This section is meant to convey both technical and sociotechnical limitations. --> |
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[More Information Needed] |
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### Recommendations |
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<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> |
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. |
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## How to Get Started with the Model |
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Use the code below to get started with the model. |
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[More Information Needed] |
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## Training Details |
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### Training Data |
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<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> |
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[More Information Needed] |
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### Training Procedure |
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<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> |
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#### Preprocessing [optional] |
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[More Information Needed] |
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#### Training Hyperparameters |
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- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> |
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#### Speeds, Sizes, Times [optional] |
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<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> |
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[More Information Needed] |
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## Evaluation |
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<!-- This section describes the evaluation protocols and provides the results. --> |
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### Testing Data, Factors & Metrics |
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#### Testing Data |
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<!-- This should link to a Dataset Card if possible. --> |
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[More Information Needed] |
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#### Factors |
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<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> |
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[More Information Needed] |
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#### Metrics |
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<!-- These are the evaluation metrics being used, ideally with a description of why. --> |
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[More Information Needed] |
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### Results |
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[More Information Needed] |
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#### Summary |
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## Model Examination [optional] |
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<!-- Relevant interpretability work for the model goes here --> |
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[More Information Needed] |
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## Environmental Impact |
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<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> |
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Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). |
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- **Hardware Type:** [More Information Needed] |
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- **Hours used:** [More Information Needed] |
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- **Cloud Provider:** [More Information Needed] |
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- **Compute Region:** [More Information Needed] |
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- **Carbon Emitted:** [More Information Needed] |
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## Technical Specifications [optional] |
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### Model Architecture and Objective |
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[More Information Needed] |
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### Compute Infrastructure |
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[More Information Needed] |
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#### Hardware |
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[More Information Needed] |
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#### Software |
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[More Information Needed] |
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## Citation [optional] |
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<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> |
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**BibTeX:** |
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[More Information Needed] |
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**APA:** |
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[More Information Needed] |
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## Glossary [optional] |
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<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> |
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[More Information Needed] |
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## More Information [optional] |
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[More Information Needed] |
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## Model Card Authors [optional] |
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[More Information Needed] |
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## Model Card Contact |
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[More Information Needed] |
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### Framework versions |
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- PEFT 0.7.1 |
