metadata
tags:
- generated_from_trainer
base_model: cardiffnlp/twitter-roberta-base-sentiment-latest
metrics:
- accuracy
model-index:
- name: fine-tuned-twitter-roberta-base-sentiment-latest
results: []
fine-tuned-twitter-roberta-base-sentiment-latest
This model is a fine-tuned version of cardiffnlp/twitter-roberta-base-sentiment-latest on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3062
- Accuracy: {'accuracy': 0.8868131868131868}
- F1score: {'f1': 0.88247351021472}
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1score |
|---|---|---|---|---|---|
| 0.461 | 0.2443 | 500 | 0.3381 | {'accuracy': 0.8565934065934065} | {'f1': 0.8483856477235431} |
| 0.3702 | 0.4885 | 1000 | 0.3378 | {'accuracy': 0.865934065934066} | {'f1': 0.8655309886906097} |
| 0.3574 | 0.7328 | 1500 | 0.2971 | {'accuracy': 0.8714285714285714} | {'f1': 0.8709435986031107} |
| 0.3358 | 0.9770 | 2000 | 0.3062 | {'accuracy': 0.8868131868131868} | {'f1': 0.88247351021472} |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1