| | --- |
| | license: apache-2.0 |
| | base_model: distilbert-base-uncased |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - emotion |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: emotion_model |
| | results: |
| | - task: |
| | name: Text Classification |
| | type: text-classification |
| | dataset: |
| | name: emotion |
| | type: emotion |
| | config: split |
| | split: test |
| | args: split |
| | metrics: |
| | - name: Accuracy |
| | type: accuracy |
| | value: 0.927 |
| | --- |
| | |
| | <!-- 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. --> |
| |
|
| | # emotion_model |
| | |
| | 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: 0.3611 |
| | - Accuracy: 0.927 |
| | |
| | ## 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: 0.0001 |
| | - train_batch_size: 16 |
| | - eval_batch_size: 16 |
| | - seed: 42 |
| | - gradient_accumulation_steps: 4 |
| | - total_train_batch_size: 64 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - lr_scheduler_warmup_ratio: 0.1 |
| | - num_epochs: 10 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | | 0.2619 | 1.0 | 250 | 0.2343 | 0.916 | |
| | | 0.121 | 2.0 | 500 | 0.1432 | 0.93 | |
| | | 0.1308 | 3.0 | 750 | 0.1565 | 0.9315 | |
| | | 0.1012 | 4.0 | 1000 | 0.1595 | 0.925 | |
| | | 0.0525 | 5.0 | 1250 | 0.1937 | 0.924 | |
| | | 0.0635 | 6.0 | 1500 | 0.2635 | 0.9255 | |
| | | 0.0183 | 7.0 | 1750 | 0.2726 | 0.9195 | |
| | | 0.0156 | 8.0 | 2000 | 0.3324 | 0.9245 | |
| | | 0.0036 | 9.0 | 2250 | 0.3614 | 0.925 | |
| | | 0.011 | 10.0 | 2500 | 0.3611 | 0.927 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.41.2 |
| | - Pytorch 2.3.0+cu121 |
| | - Datasets 2.19.2 |
| | - Tokenizers 0.19.1 |
| | |
