| --- |
| license: apache-2.0 |
| base_model: albert-base-v2 |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: ALBERT_Tweet_tuned |
| results: [] |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # ALBERT_Tweet_tuned |
|
|
| 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: 0.6621 |
| - Accuracy: 0.6684 |
|
|
| ## 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-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 | 0.56 | 100 | 0.6995 | 0.5288 | |
| | No log | 1.12 | 200 | 0.6658 | 0.6555 | |
| | No log | 1.68 | 300 | 0.6251 | 0.6660 | |
| | No log | 2.23 | 400 | 0.6158 | 0.6932 | |
| | 0.5771 | 2.79 | 500 | 0.6305 | 0.6974 | |
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|
| ### Framework versions |
|
|
| - Transformers 4.38.2 |
| - Pytorch 2.1.0+cu121 |
| - Datasets 2.18.0 |
| - Tokenizers 0.15.2 |
|
|
