distilbert-base-uncased-finetuned-btc-titles-eng
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0041
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: 5e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
0.004 | 1.0 | 2329 | 0.0286 |
0.0001 | 2.0 | 4658 | 0.0132 |
0.0 | 3.0 | 6987 | 0.0094 |
0.0 | 4.0 | 9316 | 0.0083 |
0.0002 | 5.0 | 11645 | 0.0047 |
0.144 | 6.0 | 13974 | 0.0050 |
0.0 | 7.0 | 16303 | 0.0048 |
0.0593 | 8.0 | 18632 | 0.0041 |
0.0 | 9.0 | 20961 | 0.0034 |
0.0 | 10.0 | 23290 | 0.0041 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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