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xtremedistil-l6-h256-uncased-future-time-references-D1
This model is a fine-tuned version of microsoft/xtremedistil-l6-h256-uncased on the jonaskoenig/trump_administration_statement and jonaskoenig/future-time-refernces-static-filter datsets.
It achieves the following results on the evaluation set:
- Train Loss: 0.0099
- Train Sparse Categorical Accuracy: 0.9977
- Validation Loss: 0.0128
- Validation Sparse Categorical Accuracy: 0.9976
- Epoch: 3
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:
- optimizer: {'name': 'Adam', 'learning_rate': 5e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
- training_precision: float32
Training results
| Train Loss | Train Sparse Categorical Accuracy | Validation Loss | Validation Sparse Categorical Accuracy | Epoch |
|---|---|---|---|---|
| 0.0276 | 0.9932 | 0.0156 | 0.9968 | 0 |
| 0.0138 | 0.9969 | 0.0125 | 0.9972 | 1 |
| 0.0117 | 0.9974 | 0.0126 | 0.9974 | 2 |
| 0.0099 | 0.9977 | 0.0128 | 0.9976 | 3 |
The test accuracy is: 99.77%
Framework versions
- Transformers 4.20.1
- TensorFlow 2.9.1
- Datasets 2.3.2
- Tokenizers 0.12.1
