feature_extraction_bert_v3
This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6515
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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- 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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 1.0 | 83 | 0.6953 |
| No log | 2.0 | 166 | 0.6528 |
| No log | 3.0 | 249 | 0.6403 |
| No log | 4.0 | 332 | 0.6583 |
| No log | 5.0 | 415 | 0.6589 |
| No log | 6.0 | 498 | 0.6515 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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Model tree for aakrutikatre/feature_extraction_bert_v3
Base model
google-bert/bert-base-uncased