metadata
base_model: textattack/albert-base-v2-imdb
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: nosql-identifier-albert
results: []
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