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README.md
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---
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tags:
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- generated_from_trainer
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model-index:
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- name: videberta-xsmall-finetuned-squad
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# videberta-xsmall-finetuned-squad
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This model is a fine-tuned version of [Fsoft-AIC/videberta-xsmall](https://huggingface.co/Fsoft-AIC/videberta-xsmall) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2.6690
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## 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:
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- learning_rate: 6e-05
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- train_batch_size: 16
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- eval_batch_size: 16
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_ratio: 0.05
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- num_epochs: 10
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:-----:|:-----:|:---------------:|
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| 3.0744 | 1.0 | 1196 | 2.8061 |
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| 2.432 | 2.0 | 2392 | 2.3660 |
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| 2.0159 | 3.0 | 3588 | 2.2795 |
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| 1.7175 | 4.0 | 4784 | 2.1633 |
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| 1.4843 | 5.0 | 5980 | 2.1167 |
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| 1.2682 | 6.0 | 7176 | 2.2753 |
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| 1.1 | 7.0 | 8372 | 2.4245 |
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| 0.9674 | 8.0 | 9568 | 2.5100 |
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| 0.8752 | 9.0 | 10764 | 2.6157 |
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| 0.7952 | 10.0 | 11960 | 2.6690 |
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### Framework versions
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- Transformers 4.28.0
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- Pytorch 2.0.1+cu118
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- Datasets 2.14.4
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- Tokenizers 0.13.3
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