albert-xxlarge-v2-finetuned-csqa-ih
This model is a fine-tuned version of albert-xxlarge-v2 on an unkown dataset. It achieves the following results on the evaluation set:
- Loss: 1.5694
- Accuracy: 0.8026
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: 16
- eval_batch_size: 16
- seed: 42
- 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 | Accuracy |
---|---|---|---|---|
0.8032 | 1.0 | 532 | 0.5217 | 0.8043 |
0.3182 | 2.0 | 1064 | 0.6313 | 0.7985 |
0.0668 | 3.0 | 1596 | 1.2971 | 0.7969 |
0.0131 | 4.0 | 2128 | 1.4671 | 0.8026 |
0.0046 | 5.0 | 2660 | 1.5694 | 0.8026 |
Framework versions
- Transformers 4.8.2
- Pytorch 1.9.0
- Datasets 1.10.2
- Tokenizers 0.10.3
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