| | --- |
| | license: apache-2.0 |
| | base_model: distilbert-base-uncased |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - emotion |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: pp_distilbert_ft_emotions |
| | results: |
| | - task: |
| | name: Text Classification |
| | type: text-classification |
| | dataset: |
| | name: emotion |
| | type: emotion |
| | config: split |
| | split: validation |
| | args: split |
| | metrics: |
| | - name: Accuracy |
| | type: accuracy |
| | value: 0.9275 |
| | --- |
| | |
| | <!-- 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. --> |
| |
|
| | # pp_distilbert_ft_emotions |
| | |
| | This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the emotion dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.1493 |
| | - Accuracy: 0.9275 |
| | |
| | ## 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: 5e-05 |
| | - train_batch_size: 80 |
| | - eval_batch_size: 80 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 4 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | | No log | 0.25 | 50 | 0.7329 | 0.758 | |
| | | No log | 0.5 | 100 | 0.2915 | 0.9195 | |
| | | No log | 0.75 | 150 | 0.2150 | 0.927 | |
| | | No log | 1.0 | 200 | 0.1780 | 0.9285 | |
| | | No log | 1.25 | 250 | 0.1777 | 0.9295 | |
| | | No log | 1.5 | 300 | 0.1547 | 0.937 | |
| | | No log | 1.75 | 350 | 0.1467 | 0.935 | |
| | | No log | 2.0 | 400 | 0.1446 | 0.937 | |
| | | No log | 2.25 | 450 | 0.1482 | 0.934 | |
| | | 0.3073 | 2.5 | 500 | 0.1335 | 0.9385 | |
| | | 0.3073 | 2.75 | 550 | 0.1344 | 0.9415 | |
| | | 0.3073 | 3.0 | 600 | 0.1229 | 0.9425 | |
| | | 0.3073 | 3.25 | 650 | 0.1381 | 0.939 | |
| | | 0.3073 | 3.5 | 700 | 0.1292 | 0.941 | |
| | | 0.3073 | 3.75 | 750 | 0.1278 | 0.944 | |
| | | 0.3073 | 4.0 | 800 | 0.1258 | 0.944 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.38.2 |
| | - Pytorch 2.1.0+cu121 |
| | - Datasets 2.18.0 |
| | - Tokenizers 0.15.2 |
| | |
