mega-base-fp16
This model is a fine-tuned version of mnaylor/mega-base-wikitext on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6932
- Accuracy: 0.4934
- Precision: 0.4940
- Recall: 0.5422
- F1: 0.5170
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
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
---|---|---|---|---|---|---|---|
0.6936 | 1.0 | 1074 | 0.6931 | 0.4987 | 0.4988 | 0.5442 | 0.5205 |
0.6934 | 2.0 | 2148 | 0.6932 | 0.4927 | 0.4934 | 0.5422 | 0.5167 |
0.6934 | 3.0 | 3222 | 0.6932 | 0.4934 | 0.4940 | 0.5422 | 0.5170 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
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Base model
mnaylor/mega-base-wikitext