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t5-small-ret-conceptnet2
This model is a fine-tuned version of t5-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1709
- Acc: {'accuracy': 0.8700980392156863}
- Precision: {'precision': 0.811340206185567}
- Recall: {'recall': 0.9644607843137255}
- F1: {'f1': 0.8812989921612542}
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: 1
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Acc | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.1989 | 1.0 | 721 | 0.1709 | {'accuracy': 0.8700980392156863} | {'precision': 0.811340206185567} | {'recall': 0.9644607843137255} | {'f1': 0.8812989921612542} |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu116
- Datasets 2.7.1
- Tokenizers 0.13.2
