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# albert-large-v2_squad

This model is a fine-tuned version of [albert-large-v2](https://huggingface.co/albert-large-v2) on the **squadV1** dataset.

- "eval_exact_match": 84.80605487228004
- "eval_f1": 91.80638438705844
- "eval_samples": 10808

## 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: 3e-05
- train_batch_size: 16
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0

### Training results



### Framework versions

- Transformers 4.14.1
- Pytorch 1.9.0
- Datasets 1.16.1
- Tokenizers 0.10.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["squad"], "model-index": [{"name": "albert-large-v2_squad", "results": []}]}
transformers pytorch albert question-answering generated_from_trainer dataset:squad license:apache-2.0 endpoints_compatible region:us
TAGS
#transformers #pytorch #albert #question-answering #generated_from_trainer #dataset-squad #license-apache-2.0 #endpoints_compatible #region-us 




# albert-large-v2_squad

This model is a fine-tuned version of albert-large-v2 on the squadV1 dataset.

- "eval_exact_match": 84.80605487228004
- "eval_f1": 91.80638438705844
- "eval_samples": 10808

## 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: 3e-05
- train_batch_size: 16
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0

### Training results



### Framework versions

- Transformers 4.14.1
- Pytorch 1.9.0
- Datasets 1.16.1
- Tokenizers 0.10.3

# albert-large-v2_squad

This model is a fine-tuned version of albert-large-v2 on the squadV1 dataset.

- "eval_exact_match": 84.80605487228004
- "eval_f1": 91.80638438705844
- "eval_samples": 10808 ## 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: 3e-05
- train_batch_size: 16
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0 ### Training results ### Framework versions

- Transformers 4.14.1
- Pytorch 1.9.0
- Datasets 1.16.1
- Tokenizers 0.10.3
TAGS
#transformers #pytorch #albert #question-answering #generated_from_trainer #dataset-squad #license-apache-2.0 #endpoints_compatible #region-us 
 # albert-large-v2_squad

This model is a fine-tuned version of albert-large-v2 on the squadV1 dataset.

- "eval_exact_match": 84.80605487228004
- "eval_f1": 91.80638438705844
- "eval_samples": 10808 ## 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: 3e-05
- train_batch_size: 16
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0 ### Training results ### Framework versions

- Transformers 4.14.1
- Pytorch 1.9.0
- Datasets 1.16.1
- Tokenizers 0.10.3
TAGS
#transformers #pytorch #albert #question-answering #generated_from_trainer #dataset-squad #license-apache-2.0 #endpoints_compatible #region-us 
# albert-large-v2_squad

This model is a fine-tuned version of albert-large-v2 on the squadV1 dataset.

- "eval_exact_match": 84.80605487228004
- "eval_f1": 91.80638438705844
- "eval_samples": 10808## 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: 3e-05
- train_batch_size: 16
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0### Training results### Framework versions

- Transformers 4.14.1
- Pytorch 1.9.0
- Datasets 1.16.1
- Tokenizers 0.10.3