bert_base_lda_mnli
This model is a fine-tuned version of gokulsrinivasagan/bert_base_lda on the GLUE MNLI dataset. It achieves the following results on the evaluation set:
- Loss: 1.0962
- Accuracy: 0.3295
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: 50
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.1008 | 1.0 | 1534 | 1.0993 | 0.3274 |
| 1.0986 | 2.0 | 3068 | 1.0962 | 0.3274 |
| 1.0987 | 3.0 | 4602 | 1.0989 | 0.3274 |
| 1.0985 | 4.0 | 6136 | 1.1016 | 0.3182 |
| 1.0985 | 5.0 | 7670 | 1.0989 | 0.3545 |
| 1.0988 | 6.0 | 9204 | 1.0989 | 0.3545 |
| 1.0985 | 7.0 | 10738 | 1.0968 | 0.3182 |
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