nosql-identifier-albert
This model is a fine-tuned version of textattack/albert-base-v2-imdb on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4351
- Accuracy: 0.9
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
Training results
| Training Loss |
Epoch |
Step |
Validation Loss |
Accuracy |
| No log |
1.0 |
40 |
0.4383 |
0.8 |
| No log |
2.0 |
80 |
0.3771 |
0.875 |
| No log |
3.0 |
120 |
0.2954 |
0.9 |
| No log |
4.0 |
160 |
0.3746 |
0.85 |
| No log |
5.0 |
200 |
0.4419 |
0.875 |
| No log |
6.0 |
240 |
0.4913 |
0.825 |
| No log |
7.0 |
280 |
0.4602 |
0.875 |
| No log |
8.0 |
320 |
0.4185 |
0.925 |
| No log |
9.0 |
360 |
0.5439 |
0.875 |
| No log |
10.0 |
400 |
0.4071 |
0.9 |
| No log |
11.0 |
440 |
0.5948 |
0.85 |
| No log |
12.0 |
480 |
0.5412 |
0.875 |
| 0.2697 |
13.0 |
520 |
0.5105 |
0.9 |
| 0.2697 |
14.0 |
560 |
0.4590 |
0.9 |
| 0.2697 |
15.0 |
600 |
0.4351 |
0.9 |
Framework versions
- Transformers 4.31.0
- Pytorch 1.12.1+cu113
- Datasets 2.13.1
- Tokenizers 0.11.0
