my_awesome_model
This model is a fine-tuned version of allenai/scibert_scivocab_uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1958
- Accuracy: 0.9164
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: 1
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.1482 | 0.0507 | 100 | 0.2884 | 0.9044 |
0.1465 | 0.1014 | 200 | 0.4802 | 0.8739 |
0.1523 | 0.1521 | 300 | 0.2684 | 0.8976 |
0.1454 | 0.2027 | 400 | 0.4407 | 0.8696 |
0.141 | 0.2534 | 500 | 0.2469 | 0.9106 |
0.1112 | 0.3041 | 600 | 0.3704 | 0.8927 |
0.1368 | 0.3548 | 700 | 0.3799 | 0.8878 |
0.0952 | 0.4055 | 800 | 0.3520 | 0.9041 |
0.1225 | 0.4562 | 900 | 0.3819 | 0.8882 |
0.1245 | 0.5068 | 1000 | 0.2261 | 0.9101 |
0.1479 | 0.5575 | 1100 | 0.3054 | 0.8844 |
0.1434 | 0.6082 | 1200 | 0.2268 | 0.9194 |
0.1622 | 0.6589 | 1300 | 0.2455 | 0.9053 |
0.1789 | 0.7096 | 1400 | 0.2411 | 0.8991 |
0.1832 | 0.7603 | 1500 | 0.2224 | 0.9120 |
0.1855 | 0.8109 | 1600 | 0.2102 | 0.9105 |
0.1818 | 0.8616 | 1700 | 0.1893 | 0.9211 |
0.1823 | 0.9123 | 1800 | 0.2166 | 0.9092 |
0.1632 | 0.9630 | 1900 | 0.1958 | 0.9164 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0
- Datasets 3.0.0
- Tokenizers 0.19.1
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Base model
allenai/scibert_scivocab_uncased