bert_base_lda_100_v1
This model is a fine-tuned version of on the gokulsrinivasagan/processed_wikitext-103-raw-v1-ld-100 dataset. It achieves the following results on the evaluation set:
- Loss: 6.9999
- Accuracy: 0.4235
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: 0.0001
- train_batch_size: 96
- eval_batch_size: 96
- seed: 10
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 10000
- num_epochs: 25
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
10.4589 | 4.1982 | 10000 | 10.2935 | 0.1510 |
9.6043 | 8.3963 | 20000 | 9.6179 | 0.1525 |
9.48 | 12.5945 | 30000 | 9.5449 | 0.1561 |
8.9658 | 16.7926 | 40000 | 8.8322 | 0.2303 |
7.2614 | 20.9908 | 50000 | 7.0173 | 0.4201 |
Framework versions
- Transformers 4.46.1
- Pytorch 2.2.0+cu121
- Datasets 3.1.0
- Tokenizers 0.20.1
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Dataset used to train gokulsrinivasagan/bert_base_lda_100_v1
Evaluation results
- Accuracy on gokulsrinivasagan/processed_wikitext-103-raw-v1-ld-100self-reported0.423