bert_base_lda_100_sst2
This model is a fine-tuned version of gokulsrinivasagan/bert_base_lda_100 on the GLUE SST2 dataset. It achieves the following results on the evaluation set:
- Loss: 0.6953
- Accuracy: 0.5092
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: 0.001
- train_batch_size: 256
- eval_batch_size: 256
- seed: 10
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 30
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.7015 | 1.0 | 264 | 0.6973 | 0.5092 |
0.687 | 2.0 | 528 | 0.6957 | 0.5092 |
0.6868 | 3.0 | 792 | 0.6971 | 0.5092 |
0.6867 | 4.0 | 1056 | 0.6974 | 0.5092 |
0.6866 | 5.0 | 1320 | 0.6953 | 0.5092 |
0.6864 | 6.0 | 1584 | 0.7005 | 0.5092 |
0.6865 | 7.0 | 1848 | 0.6969 | 0.5092 |
0.6865 | 8.0 | 2112 | 0.6990 | 0.5092 |
0.6868 | 9.0 | 2376 | 0.6990 | 0.5092 |
0.7886 | 10.0 | 2640 | 0.6991 | 0.5092 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.2.1+cu118
- Datasets 2.17.0
- Tokenizers 0.20.3
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gokulsrinivasagan/bert_base_lda_100