|
--- |
|
license: mit |
|
base_model: Tommert25/robbert0410_lrate7.5b32 |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- recall |
|
- accuracy |
|
model-index: |
|
- name: robbert1010_lrate7.5b32 |
|
results: [] |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
# robbert1010_lrate7.5b32 |
|
|
|
This model is a fine-tuned version of [Tommert25/robbert0410_lrate7.5b32](https://huggingface.co/Tommert25/robbert0410_lrate7.5b32) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.5187 |
|
- Precisions: 0.8552 |
|
- Recall: 0.7999 |
|
- F-measure: 0.8232 |
|
- Accuracy: 0.9157 |
|
|
|
## 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: 32 |
|
- eval_batch_size: 32 |
|
- 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 | |
|
|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:---------:|:--------:| |
|
| 0.0496 | 1.0 | 118 | 0.5283 | 0.8488 | 0.7962 | 0.8132 | 0.9092 | |
|
| 0.0474 | 2.0 | 236 | 0.4726 | 0.7961 | 0.7965 | 0.7931 | 0.9075 | |
|
| 0.026 | 3.0 | 354 | 0.5187 | 0.8552 | 0.7999 | 0.8232 | 0.9157 | |
|
| 0.0145 | 4.0 | 472 | 0.5150 | 0.8372 | 0.7791 | 0.7998 | 0.9116 | |
|
| 0.0088 | 5.0 | 590 | 0.5250 | 0.8372 | 0.7818 | 0.8021 | 0.9141 | |
|
| 0.007 | 6.0 | 708 | 0.5299 | 0.8468 | 0.7849 | 0.8072 | 0.9162 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.34.0 |
|
- Pytorch 2.0.1+cu118 |
|
- Datasets 2.14.5 |
|
- Tokenizers 0.14.1 |
|
|
