| | --- |
| | license: mit |
| | tags: |
| | - generated_from_trainer |
| | model-index: |
| | - name: feedback_intent_test |
| | results: [] |
| | --- |
| | |
| | <!-- 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. --> |
| |
|
| | # feedback_intent_test |
| |
|
| | This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset. |
| |
|
| | ## Model description |
| |
|
| | Custom data generated labeling text according to these three categories. |
| |
|
| | - Positive : Encouraging the student that they are correct and on the right track |
| | - Neutral : Mixed feedback or feedback that asks for more information |
| | - Negative : Informing the student they need to change direction or that they are not correct |
| |
|
| | Takes a user input of string text and classifies it according to one of three categories. |
| |
|
| | ## Intended uses & limitations |
| |
|
| |
|
| | from transformers import pipeline |
| | classifier = pipeline("text-classification",model="mp6kv/feedback_intent_test") |
| |
|
| |
|
| | output = classifier("great job, you're getting it!") |
| |
|
| | score = output[0]['score'] |
| |
|
| | label = output[0]['label'] |
| |
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| |
|
| | ## 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: 16 |
| | - eval_batch_size: 16 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 5 |
| |
|
| | ### Training results |
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| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.17.0 |
| | - Pytorch 1.10.0+cu111 |
| | - Datasets 1.18.3 |
| | - Tokenizers 0.11.6 |
| |
|
