distilbert-base-uncased-finetuned-mol-mlm-0.3
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: 0.7283
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 12
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
1.4456 | 1.0 | 210 | 1.0985 |
1.055 | 2.0 | 420 | 0.9764 |
0.948 | 3.0 | 630 | 0.8907 |
0.8698 | 4.0 | 840 | 0.8532 |
0.825 | 5.0 | 1050 | 0.8164 |
0.7932 | 6.0 | 1260 | 0.7907 |
0.7649 | 7.0 | 1470 | 0.7778 |
0.7469 | 8.0 | 1680 | 0.7697 |
0.7263 | 9.0 | 1890 | 0.7601 |
0.7178 | 10.0 | 2100 | 0.7385 |
0.7123 | 11.0 | 2310 | 0.7382 |
0.7074 | 12.0 | 2520 | 0.7411 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.0.1
- Datasets 2.16.1
- Tokenizers 0.15.0
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Model tree for matr1xx/distilbert-base-uncased-finetuned-mol-mlm-0.3
Base model
distilbert/distilbert-base-uncased