framing_classification_longformer
This model is a fine-tuned version of allenai/longformer-base-4096 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4961
- Accuracy: 0.9068
- F1: 0.9452
- Precision: 0.9265
- Recall: 0.9646
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: 1
- eval_batch_size: 1
- 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 | Accuracy | F1 | Precision | Recall |
---|---|---|---|---|---|---|---|
0.8485 | 1.0 | 5152 | 0.8574 | 0.8323 | 0.9085 | 0.8323 | 1.0 |
0.7968 | 2.0 | 10304 | 0.8441 | 0.8323 | 0.9085 | 0.8323 | 1.0 |
0.847 | 3.0 | 15456 | 0.8049 | 0.8323 | 0.9085 | 0.8323 | 1.0 |
0.8677 | 4.0 | 20608 | 0.7919 | 0.8323 | 0.9085 | 0.8323 | 1.0 |
0.8778 | 5.0 | 25760 | 0.8980 | 0.8323 | 0.9085 | 0.8323 | 1.0 |
0.7563 | 6.0 | 30912 | 0.8299 | 0.8323 | 0.9085 | 0.8323 | 1.0 |
0.661 | 7.0 | 36064 | 0.6065 | 0.8882 | 0.9357 | 0.8973 | 0.9776 |
0.8207 | 8.0 | 41216 | 0.5387 | 0.8975 | 0.9410 | 0.9038 | 0.9813 |
0.6872 | 9.0 | 46368 | 0.5960 | 0.8602 | 0.9212 | 0.8680 | 0.9813 |
0.4596 | 10.0 | 51520 | 0.4961 | 0.9068 | 0.9452 | 0.9265 | 0.9646 |
Framework versions
- Transformers 4.32.0.dev0
- Pytorch 2.0.1
- Datasets 2.14.4
- Tokenizers 0.13.3
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Base model
allenai/longformer-base-4096