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# fine-tuned-DatasetQAS-Squad-ID-with-xlm-roberta-large-without-ITTL-without-freeze-LR-1e-05

This model is a fine-tuned version of [xlm-roberta-large](https://huggingface.co/xlm-roberta-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3876
- Exact Match: 53.6102
- F1: 69.6077

## 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: 1e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 64
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Exact Match | F1      |
|:-------------:|:-----:|:----:|:---------------:|:-----------:|:-------:|
| 1.5313        | 0.5   | 463  | 1.4235          | 48.7014     | 66.1658 |
| 1.3868        | 1.0   | 926  | 1.3193          | 51.7189     | 68.5896 |
| 1.2618        | 1.5   | 1389 | 1.2877          | 52.8032     | 69.3561 |
| 1.1847        | 2.0   | 1852 | 1.2893          | 53.0218     | 69.7724 |
| 1.0884        | 2.5   | 2315 | 1.2777          | 53.3328     | 69.8210 |
| 1.0927        | 3.0   | 2778 | 1.2596          | 53.4000     | 69.9664 |
| 0.9519        | 3.5   | 3241 | 1.3342          | 53.6102     | 69.6168 |
| 0.9591        | 4.0   | 3704 | 1.3078          | 54.0640     | 69.9492 |
| 0.8586        | 4.49  | 4167 | 1.3876          | 53.6102     | 69.6077 |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu117
- Datasets 2.2.0
- Tokenizers 0.13.2

{"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["f1"], "model-index": [{"name": "fine-tuned-DatasetQAS-Squad-ID-with-xlm-roberta-large-without-ITTL-without-freeze-LR-1e-05", "results": []}]}
transformers pytorch tensorboard xlm-roberta question-answering generated_from_trainer license:mit endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #xlm-roberta #question-answering #generated_from_trainer #license-mit #endpoints_compatible #region-us 

fine-tuned-DatasetQAS-Squad-ID-with-xlm-roberta-large-without-ITTL-without-freeze-LR-1e-05
==========================================================================================


This model is a fine-tuned version of xlm-roberta-large on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 1.3876
* Exact Match: 53.6102
* F1: 69.6077


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: 1e-05
* train\_batch\_size: 2
* eval\_batch\_size: 2
* seed: 42
* gradient\_accumulation\_steps: 64
* total\_train\_batch\_size: 128
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10


### Training results



### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu117
* Datasets 2.2.0
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 2
* eval\_batch\_size: 2
* seed: 42
* gradient\_accumulation\_steps: 64
* total\_train\_batch\_size: 128
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10 ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu117
* Datasets 2.2.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #xlm-roberta #question-answering #generated_from_trainer #license-mit #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 2
* eval\_batch\_size: 2
* seed: 42
* gradient\_accumulation\_steps: 64
* total\_train\_batch\_size: 128
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10 ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu117
* Datasets 2.2.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #xlm-roberta #question-answering #generated_from_trainer #license-mit #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 2
* eval\_batch\_size: 2
* seed: 42
* gradient\_accumulation\_steps: 64
* total\_train\_batch\_size: 128
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10### Training results### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu117
* Datasets 2.2.0
* Tokenizers 0.13.2