metadata
base_model: Tommert25/robbert2909_lrate7.5
tags:
- generated_from_trainer
metrics:
- recall
- accuracy
model-index:
- name: robbert0210_lrate2.5
results: []
robbert0210_lrate2.5
This model is a fine-tuned version of Tommert25/robbert2909_lrate7.5 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6768
- Precisions: 0.8111
- Recall: 0.7885
- F-measure: 0.7986
- Accuracy: 0.9113
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: 2.5e-05
- train_batch_size: 4
- eval_batch_size: 4
- 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 | Precisions | Recall | F-measure | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.054 | 1.0 | 942 | 0.6914 | 0.8256 | 0.7674 | 0.7846 | 0.9065 |
| 0.0568 | 2.0 | 1884 | 0.7397 | 0.8402 | 0.7902 | 0.8075 | 0.9099 |
| 0.0423 | 3.0 | 2826 | 0.6768 | 0.8111 | 0.7885 | 0.7986 | 0.9113 |
| 0.0293 | 4.0 | 3768 | 0.7276 | 0.8138 | 0.7879 | 0.7997 | 0.9142 |
| 0.0195 | 5.0 | 4710 | 0.7553 | 0.8036 | 0.7902 | 0.7951 | 0.9109 |
| 0.0129 | 6.0 | 5652 | 0.7606 | 0.8061 | 0.7962 | 0.7999 | 0.9100 |
| 0.0051 | 7.0 | 6594 | 0.7815 | 0.8039 | 0.7993 | 0.7996 | 0.9109 |
| 0.0104 | 8.0 | 7536 | 0.7743 | 0.8077 | 0.7986 | 0.8016 | 0.9121 |
Framework versions
- Transformers 4.33.3
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3