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# yujiepan/test.mobilebert-uncased-12blks-squadv1-int8-f1-90.31

This model is a fine-tuned version of [csarron/mobilebert-uncased-squad-v1](https://huggingface.co/csarron/mobilebert-uncased-squad-v1) on the squad dataset with QAT.

### Training hyperparameters

The following hyperparameters were used during training:

-   learning_rate: 6e-05
-   train_batch_size: 32
-   eval_batch_size: 64
-   seed: 42
-   optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
-   lr_scheduler_type: cosine_with_restarts
-   num_epochs: 15.0
-   mixed_precision_training: Native AMP

### Training results

torch model:

```json
{
    "epoch": 14.82,
    "eval_exact_match": 83.66130558183538,
    "eval_f1": 90.30829859300735,
    "step": 41000
}
```

### Framework versions

-   Transformers 4.26.0
-   Pytorch 1.13.1+cu116
-   Datasets 2.8.0
-   Tokenizers 0.13.2
-   Optimum-intel 1.7.0

{"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["squad"], "model-index": [{"name": "yujiepan/test.mobilebert-uncased-12blks-squadv1-int8-f1-90.31", "results": []}]}
transformers pytorch openvino mobilebert generated_from_trainer dataset:squad license:mit endpoints_compatible region:us
TAGS
#transformers #pytorch #openvino #mobilebert #generated_from_trainer #dataset-squad #license-mit #endpoints_compatible #region-us 




# yujiepan/test.mobilebert-uncased-12blks-squadv1-int8-f1-90.31

This model is a fine-tuned version of csarron/mobilebert-uncased-squad-v1 on the squad dataset with QAT.

### Training hyperparameters

The following hyperparameters were used during training:

-   learning_rate: 6e-05
-   train_batch_size: 32
-   eval_batch_size: 64
-   seed: 42
-   optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
-   lr_scheduler_type: cosine_with_restarts
-   num_epochs: 15.0
-   mixed_precision_training: Native AMP

### Training results

torch model:



### Framework versions

-   Transformers 4.26.0
-   Pytorch 1.13.1+cu116
-   Datasets 2.8.0
-   Tokenizers 0.13.2
-   Optimum-intel 1.7.0

# yujiepan/test.mobilebert-uncased-12blks-squadv1-int8-f1-90.31

This model is a fine-tuned version of csarron/mobilebert-uncased-squad-v1 on the squad dataset with QAT. ### Training hyperparameters

The following hyperparameters were used during training:

-   learning_rate: 6e-05
-   train_batch_size: 32
-   eval_batch_size: 64
-   seed: 42
-   optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
-   lr_scheduler_type: cosine_with_restarts
-   num_epochs: 15.0
-   mixed_precision_training: Native AMP ### Training results

torch model: ### Framework versions

-   Transformers 4.26.0
-   Pytorch 1.13.1+cu116
-   Datasets 2.8.0
-   Tokenizers 0.13.2
-   Optimum-intel 1.7.0
TAGS
#transformers #pytorch #openvino #mobilebert #generated_from_trainer #dataset-squad #license-mit #endpoints_compatible #region-us 
 # yujiepan/test.mobilebert-uncased-12blks-squadv1-int8-f1-90.31

This model is a fine-tuned version of csarron/mobilebert-uncased-squad-v1 on the squad dataset with QAT. ### Training hyperparameters

The following hyperparameters were used during training:

-   learning_rate: 6e-05
-   train_batch_size: 32
-   eval_batch_size: 64
-   seed: 42
-   optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
-   lr_scheduler_type: cosine_with_restarts
-   num_epochs: 15.0
-   mixed_precision_training: Native AMP ### Training results

torch model: ### Framework versions

-   Transformers 4.26.0
-   Pytorch 1.13.1+cu116
-   Datasets 2.8.0
-   Tokenizers 0.13.2
-   Optimum-intel 1.7.0
TAGS
#transformers #pytorch #openvino #mobilebert #generated_from_trainer #dataset-squad #license-mit #endpoints_compatible #region-us 
# yujiepan/test.mobilebert-uncased-12blks-squadv1-int8-f1-90.31

This model is a fine-tuned version of csarron/mobilebert-uncased-squad-v1 on the squad dataset with QAT.### Training hyperparameters

The following hyperparameters were used during training:

-   learning_rate: 6e-05
-   train_batch_size: 32
-   eval_batch_size: 64
-   seed: 42
-   optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
-   lr_scheduler_type: cosine_with_restarts
-   num_epochs: 15.0
-   mixed_precision_training: Native AMP### Training results

torch model:### Framework versions

-   Transformers 4.26.0
-   Pytorch 1.13.1+cu116
-   Datasets 2.8.0
-   Tokenizers 0.13.2
-   Optimum-intel 1.7.0