license: apache-2.0 | |
base_model: albert-base-v2 | |
tags: | |
- generated_from_trainer | |
metrics: | |
- accuracy | |
model-index: | |
- name: AlbertIronyResults3 | |
results: [] | |
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# AlbertIronyResults3 | |
This model is a fine-tuned version of [albert-base-v2](https://huggingface.co/albert-base-v2) on an unknown dataset. | |
It achieves the following results on the evaluation set: | |
- Loss: 0.6017 | |
- Accuracy: 0.6764 | |
## 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: 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: 3 | |
### Training results | |
| Training Loss | Epoch | Step | Validation Loss | Accuracy | | |
|:-------------:|:-----:|:----:|:---------------:|:--------:| | |
| No log | 1.0 | 179 | 0.6639 | 0.5958 | | |
| No log | 2.0 | 358 | 0.6017 | 0.6764 | | |
| 0.5558 | 3.0 | 537 | 0.6362 | 0.6869 | | |
### Framework versions | |
- Transformers 4.38.2 | |
- Pytorch 2.1.0+cu121 | |
- Datasets 2.18.0 | |
- Tokenizers 0.15.2 | |