metadata
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: roberta-base
results: []
roberta-base
This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3752
- Accuracy: 0.8436
- Precision: 0.8472
- Recall: 0.8383
- F1: 0.8427
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: 1e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.5737 | 1.0 | 1074 | 0.4409 | 0.8018 | 0.8208 | 0.7723 | 0.7958 |
| 0.3689 | 2.0 | 2148 | 0.3821 | 0.8304 | 0.8398 | 0.8165 | 0.8280 |
| 0.3038 | 3.0 | 3222 | 0.3752 | 0.8436 | 0.8472 | 0.8383 | 0.8427 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0