metadata
library_name: transformers
base_model: allenai/scibert_scivocab_uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: scibert_finetuned
results: []
scibert_finetuned
This model is a fine-tuned version of allenai/scibert_scivocab_uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4315
- Accuracy: 0.8986
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.2976 | 1.0 | 138 | 0.3139 | 0.8877 |
| 0.2736 | 2.0 | 276 | 0.4315 | 0.8986 |
Framework versions
- Transformers 4.49.0.dev0
- Pytorch 2.5.1+cu118
- Datasets 3.1.0
- Tokenizers 0.21.0