| | --- |
| | license: apache-2.0 |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - tweet_eval |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: prova_Classi |
| | results: |
| | - task: |
| | name: Text Classification |
| | type: text-classification |
| | dataset: |
| | name: tweet_eval |
| | type: tweet_eval |
| | args: sentiment |
| | metrics: |
| | - name: Accuracy |
| | type: accuracy |
| | value: 0.716 |
| | --- |
| | |
| | <!-- 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. --> |
| |
|
| | # prova_Classi |
| | |
| | This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the tweet_eval dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 1.5530 |
| | - Accuracy: 0.716 |
| |
|
| | ## 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: 0.00013441028267541125 |
| | - train_batch_size: 32 |
| | - eval_batch_size: 16 |
| | - seed: 17 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 5 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | | 0.7022 | 1.0 | 1426 | 0.6581 | 0.7105 | |
| | | 0.5199 | 2.0 | 2852 | 0.6835 | 0.706 | |
| | | 0.2923 | 3.0 | 4278 | 0.7941 | 0.7075 | |
| | | 0.1366 | 4.0 | 5704 | 1.0761 | 0.7115 | |
| | | 0.0645 | 5.0 | 7130 | 1.5530 | 0.716 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.13.0 |
| | - Pytorch 1.10.0+cu111 |
| | - Datasets 1.16.1 |
| | - Tokenizers 0.10.3 |
| |
|
