metadata
license: apache-2.0
tags:
- generated_from_trainer
base_model: bert-base-multilingual-cased
metrics:
- accuracy
model-index:
- name: fine-tune-berta-TOG-split-headline1
results: []
fine-tune-berta-TOG-split-headline1
This model is a fine-tuned version of bert-base-multilingual-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.1203
- Accuracy: 0.3876
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: 32
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 7
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
1.0797 | 1.0 | 27 | 1.0941 | 0.3828 |
1.0888 | 2.0 | 54 | 1.0949 | 0.3828 |
1.0863 | 3.0 | 81 | 1.0958 | 0.3828 |
1.0757 | 4.0 | 108 | 1.1015 | 0.3923 |
1.0443 | 5.0 | 135 | 1.0944 | 0.3732 |
1.0329 | 6.0 | 162 | 1.1091 | 0.3732 |
0.9922 | 7.0 | 189 | 1.1203 | 0.3876 |
Framework versions
- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1