metadata
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
- precision
- recall
model-index:
- name: rating-classifier
results: []
rating-classifier
This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- F1: 0.6729
- Loss: 0.8373
- Accuracy: 0.6710
- Precision: 0.6774
- Recall: 0.6710
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
- lr_scheduler_warmup_steps: 500
- num_epochs: 5
Training results
Training Loss | Epoch | Step | F1 | Validation Loss | Accuracy | Precision | Recall |
---|---|---|---|---|---|---|---|
1.0326 | 1.0 | 984 | 0.6354 | 0.8096 | 0.6707 | 0.6383 | 0.6707 |
0.6801 | 2.0 | 1968 | 0.6668 | 0.7508 | 0.6888 | 0.6667 | 0.6888 |
0.5313 | 3.0 | 2952 | 0.6729 | 0.8373 | 0.6710 | 0.6774 | 0.6710 |
0.3895 | 4.0 | 3936 | 0.6678 | 0.9705 | 0.6730 | 0.6649 | 0.6730 |
0.2857 | 5.0 | 4920 | 0.6708 | 1.0989 | 0.6745 | 0.6684 | 0.6745 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1