| --- |
| base_model: Fsoft-AIC/videberta-base |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: ComOM-VIDeBERTa-2 |
| 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. --> |
|
|
| # ComOM-VIDeBERTa-2 |
|
|
| This model is a fine-tuned version of [Fsoft-AIC/videberta-base](https://huggingface.co/Fsoft-AIC/videberta-base) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 1.3046 |
| - Accuracy: 0.5357 |
|
|
| ## Model description |
|
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| More information needed |
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|
| ## Intended uses & limitations |
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|
| More information needed |
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| ## Training and evaluation data |
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| More information needed |
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|
| ## Training procedure |
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|
| ### Training hyperparameters |
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| 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: 8 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | No log | 1.0 | 77 | 1.4249 | 0.4708 | |
| | No log | 2.0 | 154 | 1.4096 | 0.4708 | |
| | No log | 3.0 | 231 | 1.3871 | 0.4708 | |
| | No log | 4.0 | 308 | 1.3809 | 0.5032 | |
| | No log | 5.0 | 385 | 1.3529 | 0.5195 | |
| | No log | 6.0 | 462 | 1.3257 | 0.5260 | |
| | 1.4302 | 7.0 | 539 | 1.3101 | 0.5325 | |
| | 1.4302 | 8.0 | 616 | 1.3046 | 0.5357 | |
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| ### Framework versions |
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|
| - Transformers 4.35.0 |
| - Pytorch 2.0.0 |
| - Datasets 2.1.0 |
| - Tokenizers 0.14.1 |
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|
