Fixed parameters:
* **model_name_or_path**: `Bhumika/roberta-base-finetuned-sst2`
* **dataset**:
    * **path**: `glue`
    * **name**: `sst2`
    * **calibration_split**: `None`
    * **eval_split**: `validation`
    * **data_keys**: `['sentence']`
    * **label_keys**: `['label']`
* **quantization_approach**: `dynamic`
* **node_exclusion**: `[]`
* **per_channel**: `False`
* **calibration**: `None`
* **framework**: `onnxruntime`
* **framework_args**:
    * **opset**: `15`
    * **optimization_level**: `1`
* **aware_training**: `False`

Benchmarked parameters:
* **operators_to_quantize**: `['Add', 'MatMul']`, `['Add']`

## Evaluation
Below, time metrics for
* Batch size: 8
* Input length: 128
| operators_to_quantize |     | latency_mean (original, ms) | latency_mean (optimized, ms) |     | throughput (original, /s) | throughput (optimized, /s) |     | accuracy (original) | accuracy (optimized) |
| :-------------------: | :-: | :-------------------------: | :--------------------------: | :-: | :-----------------------: | :------------------------: | :-: | :-----------------: | :------------------: |
|       `['Add']`       |  \|  |           454.70            |            361.81            |  \|  |           2.50            |            3.00            |  \|  |         1.0         |         1.0          |
|  `['Add', 'MatMul']`  |  \|  |           474.54            |            135.14            |  \|  |           2.50            |            7.50            |  \|  |         1.0         |         1.0          |

{}
region:us
TAGS
#region-us 

Fixed parameters:
* model_name_or_path: 'Bhumika/roberta-base-finetuned-sst2'
* dataset:
    * path: 'glue'
    * name: 'sst2'
    * calibration_split: 'None'
    * eval_split: 'validation'
    * data_keys: '['sentence']'
    * label_keys: '['label']'
* quantization_approach: 'dynamic'
* node_exclusion: '[]'
* per_channel: 'False'
* calibration: 'None'
* framework: 'onnxruntime'
* framework_args:
    * opset: '15'
    * optimization_level: '1'
* aware_training: 'False'

Benchmarked parameters:
* operators_to_quantize: '['Add', 'MatMul']', '['Add']'

## Evaluation
Below, time metrics for
* Batch size: 8
* Input length: 128
| operators_to_quantize |     | latency_mean (original, ms) | latency_mean (optimized, ms) |     | throughput (original, /s) | throughput (optimized, /s) |     | accuracy (original) | accuracy (optimized) |
| :-------------------: | :-: | :-------------------------: | :--------------------------: | :-: | :-----------------------: | :------------------------: | :-: | :-----------------: | :------------------: |
|       '['Add']'       |  \|  |           454.70            |            361.81            |  \|  |           2.50            |            3.00            |  \|  |         1.0         |         1.0          |
|  '['Add', 'MatMul']'  |  \|  |           474.54            |            135.14            |  \|  |           2.50            |            7.50            |  \|  |         1.0         |         1.0          |

## Evaluation
Below, time metrics for
* Batch size: 8
* Input length: 128
| operators_to_quantize |     | latency_mean (original, ms) | latency_mean (optimized, ms) |     | throughput (original, /s) | throughput (optimized, /s) |     | accuracy (original) | accuracy (optimized) |
| :-------------------: | :-: | :-------------------------: | :--------------------------: | :-: | :-----------------------: | :------------------------: | :-: | :-----------------: | :------------------: |
|       '['Add']'       |  \|  |           454.70            |            361.81            |  \|  |           2.50            |            3.00            |  \|  |         1.0         |         1.0          |
|  '['Add', 'MatMul']'  |  \|  |           474.54            |            135.14            |  \|  |           2.50            |            7.50            |  \|  |         1.0         |         1.0          |
TAGS
#region-us 
 ## Evaluation
Below, time metrics for
* Batch size: 8
* Input length: 128
| operators_to_quantize |     | latency_mean (original, ms) | latency_mean (optimized, ms) |     | throughput (original, /s) | throughput (optimized, /s) |     | accuracy (original) | accuracy (optimized) |
| :-------------------: | :-: | :-------------------------: | :--------------------------: | :-: | :-----------------------: | :------------------------: | :-: | :-----------------: | :------------------: |
|       '['Add']'       |  \|  |           454.70            |            361.81            |  \|  |           2.50            |            3.00            |  \|  |         1.0         |         1.0          |
|  '['Add', 'MatMul']'  |  \|  |           474.54            |            135.14            |  \|  |           2.50            |            7.50            |  \|  |         1.0         |         1.0          |
passage: TAGS
#region-us 
## Evaluation
Below, time metrics for
* Batch size: 8
* Input length: 128
| operators_to_quantize |     | latency_mean (original, ms) | latency_mean (optimized, ms) |     | throughput (original, /s) | throughput (optimized, /s) |     | accuracy (original) | accuracy (optimized) |
| :-------------------: | :-: | :-------------------------: | :--------------------------: | :-: | :-----------------------: | :------------------------: | :-: | :-----------------: | :------------------: |
|       '['Add']'       |  \|  |           454.70            |            361.81            |  \|  |           2.50            |            3.00            |  \|  |         1.0         |         1.0          |
|  '['Add', 'MatMul']'  |  \|  |           474.54            |            135.14            |  \|  |           2.50            |            7.50            |  \|  |         1.0         |         1.0          |