metadata
license: mit
base_model: Tommert25/robbert1010_lrate7.5b8
tags:
- generated_from_trainer
metrics:
- recall
- accuracy
model-index:
- name: robbert1010_lrate7.5b8
results: []
robbert1010_lrate7.5b8
This model is a fine-tuned version of Tommert25/robbert1010_lrate7.5b8 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6507
- Precisions: 0.8092
- Recall: 0.7854
- F-measure: 0.7957
- Accuracy: 0.9171
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: 7.5e-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: 6
Training results
| Training Loss | Epoch | Step | Validation Loss | Precisions | Recall | F-measure | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.0839 | 1.0 | 471 | 0.5608 | 0.8220 | 0.7659 | 0.7824 | 0.9082 |
| 0.0762 | 2.0 | 942 | 0.5485 | 0.8290 | 0.7683 | 0.7743 | 0.9086 |
| 0.0412 | 3.0 | 1413 | 0.6303 | 0.7841 | 0.7745 | 0.7780 | 0.9090 |
| 0.0352 | 4.0 | 1884 | 0.6346 | 0.7978 | 0.7831 | 0.7893 | 0.9109 |
| 0.0251 | 5.0 | 2355 | 0.6494 | 0.7956 | 0.7878 | 0.7911 | 0.9138 |
| 0.0138 | 6.0 | 2826 | 0.6507 | 0.8092 | 0.7854 | 0.7957 | 0.9171 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1