fine-tuning-albert-tiny-041123
This model is a fine-tuned version of dccuchile/albert-tiny-spanish on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.2027
- Precision: 0.1111
- F1: 0.1667
- Recall: 0.3333
- Accuracy: 0.3333
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: 5e-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: 8
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | F1 | Recall | Accuracy |
---|---|---|---|---|---|---|---|
1.034 | 1.0 | 1304 | 1.2027 | 0.1111 | 0.1667 | 0.3333 | 0.3333 |
1.0266 | 2.0 | 2608 | 1.1847 | 0.1111 | 0.1667 | 0.3333 | 0.3333 |
1.0248 | 3.0 | 3912 | 1.1969 | 0.1111 | 0.1667 | 0.3333 | 0.3333 |
1.0317 | 4.0 | 5216 | 1.2050 | 0.1111 | 0.1667 | 0.3333 | 0.3333 |
1.0285 | 5.0 | 6520 | 1.1994 | 0.1111 | 0.1667 | 0.3333 | 0.3333 |
1.0281 | 6.0 | 7824 | 1.1928 | 0.1111 | 0.1667 | 0.3333 | 0.3333 |
1.0216 | 7.0 | 9128 | 1.2110 | 0.1111 | 0.1667 | 0.3333 | 0.3333 |
1.0268 | 8.0 | 10432 | 1.2035 | 0.1111 | 0.1667 | 0.3333 | 0.3333 |
Framework versions
- Transformers 4.27.4
- Pytorch 1.13.1+cu116
- Datasets 2.11.0
- Tokenizers 0.13.3
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