metadata
license: apache-2.0
base_model: albert-base-v2
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: results
results: []
results
This model is a fine-tuned version of albert-base-v2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.7940
- Accuracy: 0.6556
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: 7.45e-06
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 179 | 0.6503 | 0.6492 |
| No log | 2.0 | 358 | 0.7322 | 0.6565 |
| 0.4518 | 3.0 | 537 | 0.7242 | 0.6649 |
| 0.4518 | 4.0 | 716 | 0.7997 | 0.6586 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2