olm-bert-tiny-december-2022-target-glue-mnli
This model is a fine-tuned version of muhtasham/olm-bert-tiny-december-2022 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.9980
- Accuracy: 0.5011
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: 3e-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: constant
- training_steps: 5000
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
1.0986 | 0.04 | 500 | 1.0979 | 0.3509 |
1.098 | 0.08 | 1000 | 1.0988 | 0.3344 |
1.083 | 0.12 | 1500 | 1.0572 | 0.4546 |
1.0527 | 0.16 | 2000 | 1.0380 | 0.4709 |
1.0447 | 0.2 | 2500 | 1.0279 | 0.4759 |
1.0343 | 0.24 | 3000 | 1.0261 | 0.4724 |
1.0266 | 0.29 | 3500 | 1.0158 | 0.4808 |
1.0199 | 0.33 | 4000 | 1.0120 | 0.4841 |
1.0141 | 0.37 | 4500 | 1.0022 | 0.4924 |
1.0051 | 0.41 | 5000 | 0.9980 | 0.5011 |
Framework versions
- Transformers 4.27.0.dev0
- Pytorch 1.13.1+cu116
- Datasets 2.9.1.dev0
- Tokenizers 0.13.2
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