metadata
base_model: allenai/biomed_roberta_base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: biomed_roberta_all_deep
results: []
biomed_roberta_all_deep
This model is a fine-tuned version of allenai/biomed_roberta_base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.7519
- Precision: 0.6732
- Recall: 0.7142
- F1: 0.6931
- Accuracy: 0.8255
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: 8
- eval_batch_size: 8
- 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 | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 363 | 0.5600 | 0.6059 | 0.6773 | 0.6396 | 0.8131 |
| 0.7102 | 2.0 | 726 | 0.5290 | 0.6310 | 0.7172 | 0.6713 | 0.8248 |
| 0.4147 | 3.0 | 1089 | 0.5253 | 0.6620 | 0.7075 | 0.6840 | 0.8289 |
| 0.4147 | 4.0 | 1452 | 0.5572 | 0.6664 | 0.7062 | 0.6857 | 0.8263 |
| 0.3081 | 5.0 | 1815 | 0.5942 | 0.6615 | 0.7127 | 0.6862 | 0.8244 |
| 0.231 | 6.0 | 2178 | 0.6393 | 0.6745 | 0.7064 | 0.6901 | 0.8268 |
| 0.1864 | 7.0 | 2541 | 0.6771 | 0.6769 | 0.7050 | 0.6907 | 0.8250 |
| 0.1864 | 8.0 | 2904 | 0.7091 | 0.6708 | 0.7120 | 0.6908 | 0.8263 |
| 0.1523 | 9.0 | 3267 | 0.7463 | 0.6702 | 0.7159 | 0.6923 | 0.8255 |
| 0.1336 | 10.0 | 3630 | 0.7519 | 0.6732 | 0.7142 | 0.6931 | 0.8255 |
Framework versions
- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1