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# fine-tuned-DatasetQAS-TYDI-QA-ID-with-xlm-roberta-large-with-ITTL-with-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: 0.9154
- Exact Match: 67.4296
- F1: 80.7483

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 16
- 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      |
|:-------------:|:-----:|:----:|:---------------:|:-----------:|:-------:|
| 6.331         | 0.5   | 19   | 3.7275          | 5.2817      | 16.4975 |
| 6.331         | 0.99  | 38   | 2.5293          | 22.3592     | 33.2570 |
| 3.6805        | 1.5   | 57   | 1.5504          | 45.4225     | 61.5302 |
| 3.6805        | 1.99  | 76   | 1.2025          | 57.2183     | 72.1651 |
| 3.6805        | 2.5   | 95   | 1.0664          | 61.0915     | 75.6496 |
| 1.3982        | 2.99  | 114  | 0.9926          | 63.2042     | 77.6464 |
| 1.3982        | 3.5   | 133  | 0.9823          | 64.6127     | 78.3848 |
| 0.9533        | 3.99  | 152  | 0.9596          | 66.1972     | 79.5651 |
| 0.9533        | 4.5   | 171  | 0.9578          | 67.4296     | 80.6710 |
| 0.9533        | 4.99  | 190  | 0.9376          | 68.3099     | 80.8025 |
| 0.7418        | 5.5   | 209  | 0.9393          | 67.4296     | 79.8821 |
| 0.7418        | 5.99  | 228  | 0.9242          | 67.4296     | 79.9318 |
| 0.7418        | 6.5   | 247  | 0.9154          | 67.4296     | 80.7483 |


### 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-TYDI-QA-ID-with-xlm-roberta-large-with-ITTL-with-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-TYDI-QA-ID-with-xlm-roberta-large-with-ITTL-with-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: 0.9154
* Exact Match: 67.4296
* F1: 80.7483


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: 8
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 16
* 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: 8
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 16
* 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: 8
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 16
* 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