finetuning-sentiment-model-1000-samples
This model is a fine-tuned version of finiteautomata/bertweet-base-sentiment-analysis on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0307
- Accuracy: 0.9962
- F1: 0.9965
- Recall: 1.0
- Precision: 0.9931
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: 2
Training results
Framework versions
- Transformers 4.39.3
- Pytorch 1.13.1+cpu
- Datasets 2.18.0
- Tokenizers 0.15.2
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