metadata
license: mit
base_model: google-bert/bert-base-german-cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: BERT_Reciever_6
results: []
BERT_Reciever_6
This model is a fine-tuned version of google-bert/bert-base-german-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1356
- Accuracy: 0.9561
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: 0.0001
- train_batch_size: 160
- eval_batch_size: 160
- seed: 2805
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 31 | 0.3889 | 0.9196 |
| No log | 2.0 | 62 | 0.2137 | 0.9342 |
| No log | 3.0 | 93 | 0.1763 | 0.9433 |
| No log | 4.0 | 124 | 0.1660 | 0.9433 |
| No log | 5.0 | 155 | 0.1592 | 0.9415 |
| No log | 6.0 | 186 | 0.1522 | 0.9470 |
| No log | 7.0 | 217 | 0.1454 | 0.9525 |
| No log | 8.0 | 248 | 0.1448 | 0.9506 |
| No log | 9.0 | 279 | 0.1388 | 0.9525 |
| No log | 10.0 | 310 | 0.1356 | 0.9561 |
Framework versions
- Transformers 4.44.0.dev0
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1