TAM-10epoch-BertMul
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: 1.1285
- Accuracy: 0.4340
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: 10
- eval_batch_size: 10
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss |
Epoch |
Step |
Validation Loss |
Accuracy |
| No log |
1.0 |
8 |
1.1051 |
0.2264 |
| No log |
2.0 |
16 |
1.0816 |
0.5094 |
| No log |
3.0 |
24 |
1.0964 |
0.6415 |
| No log |
4.0 |
32 |
1.1052 |
0.4151 |
| No log |
5.0 |
40 |
1.0832 |
0.4340 |
| No log |
6.0 |
48 |
1.0855 |
0.4151 |
| No log |
7.0 |
56 |
1.1034 |
0.4528 |
| No log |
8.0 |
64 |
1.1136 |
0.4340 |
| No log |
9.0 |
72 |
1.1246 |
0.4340 |
| No log |
10.0 |
80 |
1.1285 |
0.4340 |
Framework versions
- Transformers 4.35.0.dev0
- Pytorch 1.13.1
- Datasets 2.14.5
- Tokenizers 0.14.1
