t5-en-vi-small-ed-multi
This model is a fine-tuned version of NlpHUST/t5-en-vi-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 42.1043
- F1 Micro: 0.0
- Recall Micro: 0.0
- Precision Micro: 0.0
- F1 Macro: 0.0
- Recall Macro: 0.0
- Precision Macro: 0.0
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 Micro | Recall Micro | Precision Micro | F1 Macro | Recall Macro | Precision Macro |
|---|---|---|---|---|---|---|---|---|---|
| No log | 0.9987 | 393 | 42.1043 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 0.0 | 2.0 | 787 | 42.1043 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 0.0 | 2.9987 | 1180 | 42.1043 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 0.0 | 4.0 | 1574 | 42.1043 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 0.0 | 4.9936 | 1965 | 42.1043 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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Model tree for cuongpp/t5-en-vi-small-ed-multi
Base model
NlpHUST/t5-en-vi-small