| --- |
| tags: |
| - generated_from_trainer |
| metrics: |
| - f1 |
| - recall |
| - precision |
| model-index: |
| - name: sentiment-roberta_base-e4-b16 |
| 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. --> |
|
|
| # sentiment-roberta_base-e4-b16 |
| |
| This model is a fine-tuned version of [cardiffnlp/twitter-roberta-base-sentiment](https://huggingface.co/cardiffnlp/twitter-roberta-base-sentiment) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 1.6110 |
| - F1: 0.7385 |
| - Recall: 0.7385 |
| - Precision: 0.7385 |
| |
| ## 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: 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: 4 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | F1 | Recall | Precision | |
| |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:---------:| |
| | No log | 1.0 | 375 | 0.8888 | 0.7493 | 0.7493 | 0.7493 | |
| | 0.461 | 2.0 | 750 | 1.1518 | 0.7493 | 0.7493 | 0.7493 | |
| | 0.1578 | 3.0 | 1125 | 1.5342 | 0.7358 | 0.7358 | 0.7358 | |
| | 0.0658 | 4.0 | 1500 | 1.6110 | 0.7385 | 0.7385 | 0.7385 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.30.2 |
| - Pytorch 2.0.1+cu118 |
| - Datasets 2.13.1 |
| - Tokenizers 0.13.3 |
| |
