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# albert-base-v2-finetuned-squad

This model is a fine-tuned version of [albert-base-v2](https://huggingface.co/albert-base-v2) on the squad_v2 dataset.
It achieves the following results on the evaluation set:
- Loss: 3.5840

## 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: 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: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log        | 1.0   | 313  | 1.2505          |
| 1.5439        | 2.0   | 626  | 1.1598          |
| 1.5439        | 3.0   | 939  | 1.2708          |
| 0.7133        | 4.0   | 1252 | 1.5814          |
| 0.3044        | 5.0   | 1565 | 2.0296          |
| 0.3044        | 6.0   | 1878 | 2.2515          |
| 0.1225        | 7.0   | 2191 | 2.4035          |
| 0.0586        | 8.0   | 2504 | 2.8478          |
| 0.0586        | 9.0   | 2817 | 3.0978          |
| 0.0225        | 10.0  | 3130 | 3.5416          |
| 0.0225        | 11.0  | 3443 | 3.5272          |
| 0.0071        | 12.0  | 3756 | 3.5285          |
| 0.0013        | 13.0  | 4069 | 3.5399          |
| 0.0013        | 14.0  | 4382 | 3.5729          |
| 0.0007        | 15.0  | 4695 | 3.5840          |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["squad_v2"], "model-index": [{"name": "albert-base-v2-finetuned-squad", "results": []}]}
transformers pytorch tensorboard albert question-answering generated_from_trainer dataset:squad_v2 license:apache-2.0 endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #albert #question-answering #generated_from_trainer #dataset-squad_v2 #license-apache-2.0 #endpoints_compatible #region-us 

albert-base-v2-finetuned-squad
==============================


This model is a fine-tuned version of albert-base-v2 on the squad\_v2 dataset.
It achieves the following results on the evaluation set:


* Loss: 3.5840


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: 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: 15


### Training results



### Framework versions


* Transformers 4.30.2
* Pytorch 2.0.1+cu118
* Datasets 2.13.1
* Tokenizers 0.13.3



### Training hyperparameters


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: 15 ### Training results ### Framework versions


* Transformers 4.30.2
* Pytorch 2.0.1+cu118
* Datasets 2.13.1
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #albert #question-answering #generated_from_trainer #dataset-squad_v2 #license-apache-2.0 #endpoints_compatible #region-us 
 ### Training hyperparameters


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: 15 ### Training results ### Framework versions


* Transformers 4.30.2
* Pytorch 2.0.1+cu118
* Datasets 2.13.1
* Tokenizers 0.13.3