---
license: mit
base_model: csarron/mobilebert-uncased-squad-v2
tags:
- generated_from_trainer
model-index:
- name: mobilebert-uncased-squad-v2-30-10-22
  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. -->

# mobilebert-uncased-squad-v2-30-10-22

This model is a fine-tuned version of [csarron/mobilebert-uncased-squad-v2](https://huggingface.co/csarron/mobilebert-uncased-squad-v2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 13.5041

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log        | 1.0   | 228  | 3.1250          |
| No log        | 2.0   | 456  | 3.5844          |
| 1.1867        | 3.0   | 684  | 3.9242          |
| 1.1867        | 4.0   | 912  | 4.4160          |
| 0.842         | 5.0   | 1140 | 5.3645          |
| 0.842         | 6.0   | 1368 | 5.7769          |
| 0.5983        | 7.0   | 1596 | 5.6078          |
| 0.5983        | 8.0   | 1824 | 6.2784          |
| 0.4518        | 9.0   | 2052 | 7.7741          |
| 0.4518        | 10.0  | 2280 | 7.4468          |
| 0.332         | 11.0  | 2508 | 8.0155          |
| 0.332         | 12.0  | 2736 | 9.0584          |
| 0.332         | 13.0  | 2964 | 9.9912          |
| 0.2125        | 14.0  | 3192 | 11.2215         |
| 0.2125        | 15.0  | 3420 | 11.8451         |
| 0.1525        | 16.0  | 3648 | 12.2774         |
| 0.1525        | 17.0  | 3876 | 12.5938         |
| 0.1232        | 18.0  | 4104 | 13.8241         |
| 0.1232        | 19.0  | 4332 | 13.4653         |
| 0.1152        | 20.0  | 4560 | 13.5041         |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1