metadata
license: mit
base_model: xlnet-base-cased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: IMDB-XLNet-CLSModel_v3
results: []
IMDB-XLNet-CLSModel_v3
This model is a fine-tuned version of xlnet-base-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1544
- Accuracy: 0.9466
- F1: 0.9466
- Precision: 0.9467
- Recall: 0.9466
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: 5e-06
- 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
- lr_scheduler_warmup_steps: 100
- num_epochs: 1
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
---|---|---|---|---|---|---|---|
No log | 0.3836 | 300 | 0.1660 | 0.9406 | 0.9406 | 0.9413 | 0.9406 |
0.2833 | 0.7673 | 600 | 0.1544 | 0.9466 | 0.9466 | 0.9467 | 0.9466 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1