---
tags:
- generated_from_trainer
model-index:
- name: videberta-xsmall-finetuned-squad
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# videberta-xsmall-finetuned-squad

This model is a fine-tuned version of [Fsoft-AIC/videberta-xsmall](https://huggingface.co/Fsoft-AIC/videberta-xsmall) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.6690

## 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: 6e-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
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 3.0744        | 1.0   | 1196  | 2.8061          |
| 2.432         | 2.0   | 2392  | 2.3660          |
| 2.0159        | 3.0   | 3588  | 2.2795          |
| 1.7175        | 4.0   | 4784  | 2.1633          |
| 1.4843        | 5.0   | 5980  | 2.1167          |
| 1.2682        | 6.0   | 7176  | 2.2753          |
| 1.1           | 7.0   | 8372  | 2.4245          |
| 0.9674        | 8.0   | 9568  | 2.5100          |
| 0.8752        | 9.0   | 10764 | 2.6157          |
| 0.7952        | 10.0  | 11960 | 2.6690          |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3