zindi-hqa-mt0
This model is a fine-tuned version of bigscience/mt0-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.2584
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: 0.0005
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAFACTOR and the args are: No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 3.4547 | 1.0 | 1864 | 1.5158 |
| 2.8687 | 2.0 | 3728 | 1.3227 |
| 2.6186 | 3.0 | 5592 | 1.2584 |
Framework versions
- Transformers 5.12.1
- Pytorch 2.11.0+cu128
- Datasets 5.0.0
- Tokenizers 0.22.2
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