metadata
base_model: allenai/scibert_scivocab_uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: impact-cat
results: []
impact-cat
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: 0.8264
- Accuracy: 0.725
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 40 | 1.1896 | 0.5375 |
| No log | 2.0 | 80 | 0.6831 | 0.7 |
| No log | 3.0 | 120 | 0.6951 | 0.7 |
| No log | 4.0 | 160 | 0.7126 | 0.6937 |
| No log | 5.0 | 200 | 0.7937 | 0.6875 |
| No log | 6.0 | 240 | 0.6445 | 0.7125 |
| No log | 7.0 | 280 | 0.7990 | 0.7188 |
| No log | 8.0 | 320 | 0.8264 | 0.725 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2