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# albert-large-v2-spoken-squad

This model is a fine-tuned version of [albert-large-v2](https://huggingface.co/albert-large-v2) on the [Spoken Squad](https://github.com/chiahsuan156/Spoken-SQuAD) dataset.
It achieves the following results on the evaluation set:
- Exact Match: 66.7026
- F1: 79.3491
- Loss: 1.0481

## Model description

Results on Spoken Squad Test Sets

| Test Set      | Test Loss | Samples | Exact Match | F1      |
|:-------------:|:---------:|:-------:|:-----------:|:-------:|
| Test          | 1.183     | 5351    | 71.2951     | 80.4348 |
| Test WER44    | 6.2158    | 5351    | 45.9727     | 60.8491 |
| Test WER54    | 6.2158    | 5351    | 45.9727     | 60.8491 |

## 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: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Exact Match | F1      | Validation Loss |
|:-------------:|:-----:|:----:|:-----------:|:-------:|:---------------:|
| 1.0444        | 1.0   | 2088 | 63.6584     | 77.0975 | 1.0645          |
| 0.8017        | 2.0   | 4176 | 66.3524     | 79.3253 | 0.9756          |
| 0.5426        | 3.0   | 6264 | 66.7026     | 79.3491 | 1.0481          |


### Framework versions

- Transformers 4.24.0
- Pytorch 1.13.1
- Datasets 2.8.0
- Tokenizers 0.11.0

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["f1"], "model-index": [{"name": "albert-large-v2-spoken-squad", "results": []}]}
transformers pytorch albert question-answering generated_from_trainer license:apache-2.0 endpoints_compatible region:us
TAGS
#transformers #pytorch #albert #question-answering #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us 

albert-large-v2-spoken-squad
============================


This model is a fine-tuned version of albert-large-v2 on the Spoken Squad dataset.
It achieves the following results on the evaluation set:


* Exact Match: 66.7026
* F1: 79.3491
* Loss: 1.0481


Model description
-----------------


Results on Spoken Squad Test Sets



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: 64
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.24.0
* Pytorch 1.13.1
* Datasets 2.8.0
* Tokenizers 0.11.0



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 16
* eval\_batch\_size: 64
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.24.0
* Pytorch 1.13.1
* Datasets 2.8.0
* Tokenizers 0.11.0
TAGS
#transformers #pytorch #albert #question-answering #generated_from_trainer #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: 64
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.24.0
* Pytorch 1.13.1
* Datasets 2.8.0
* Tokenizers 0.11.0
TAGS
#transformers #pytorch #albert #question-answering #generated_from_trainer #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: 64
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.24.0
* Pytorch 1.13.1
* Datasets 2.8.0
* Tokenizers 0.11.0