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# greek-nllb-4ep-384

This model is a fine-tuned version of [facebook/nllb-200-distilled-600M](https://huggingface.co/facebook/nllb-200-distilled-600M) on the squad dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2875

## 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: 0.0001
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.215         | 0.17  | 100  | 1.5536          |
| 1.7149        | 0.34  | 200  | 1.4819          |
| 1.544         | 0.51  | 300  | 1.4381          |
| 1.5006        | 0.67  | 400  | 1.3999          |
| 1.4577        | 0.84  | 500  | 1.3756          |
| 1.4495        | 1.01  | 600  | 1.3613          |
| 1.32          | 1.18  | 700  | 1.3467          |
| 1.2999        | 1.35  | 800  | 1.3404          |
| 1.2993        | 1.52  | 900  | 1.3339          |
| 1.2909        | 1.69  | 1000 | 1.3189          |
| 1.2974        | 1.86  | 1100 | 1.3112          |
| 1.2516        | 2.03  | 1200 | 1.3171          |
| 1.1852        | 2.2   | 1300 | 1.3032          |
| 1.1862        | 2.36  | 1400 | 1.3072          |
| 1.184         | 2.53  | 1500 | 1.2967          |
| 1.1865        | 2.7   | 1600 | 1.2968          |
| 1.1797        | 2.87  | 1700 | 1.2903          |
| 1.1707        | 3.04  | 1800 | 1.2934          |
| 1.1128        | 3.21  | 1900 | 1.2927          |
| 1.1314        | 3.38  | 2000 | 1.2895          |
| 1.1141        | 3.55  | 2100 | 1.2889          |
| 1.1137        | 3.72  | 2200 | 1.2888          |
| 1.1069        | 3.88  | 2300 | 1.2875          |


### Framework versions

- Transformers 4.27.0.dev0
- Pytorch 1.13.0
- Datasets 2.1.0
- Tokenizers 0.13.2

{"license": "cc-by-nc-4.0", "tags": ["generated_from_trainer"], "datasets": ["squad"], "model-index": [{"name": "greek-nllb-4ep-384", "results": []}]}
transformers pytorch m2m_100 text2text-generation generated_from_trainer dataset:squad license:cc-by-nc-4.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #m2m_100 #text2text-generation #generated_from_trainer #dataset-squad #license-cc-by-nc-4.0 #autotrain_compatible #endpoints_compatible #region-us 

greek-nllb-4ep-384
==================


This model is a fine-tuned version of facebook/nllb-200-distilled-600M on the squad dataset.
It achieves the following results on the evaluation set:


* Loss: 1.2875


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: 0.0001
* train\_batch\_size: 2
* eval\_batch\_size: 2
* seed: 42
* gradient\_accumulation\_steps: 16
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 4


### Training results



### Framework versions


* Transformers 4.27.0.dev0
* Pytorch 1.13.0
* Datasets 2.1.0
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0001
* train\_batch\_size: 2
* eval\_batch\_size: 2
* seed: 42
* gradient\_accumulation\_steps: 16
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 4 ### Training results ### Framework versions


* Transformers 4.27.0.dev0
* Pytorch 1.13.0
* Datasets 2.1.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #m2m_100 #text2text-generation #generated_from_trainer #dataset-squad #license-cc-by-nc-4.0 #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0001
* train\_batch\_size: 2
* eval\_batch\_size: 2
* seed: 42
* gradient\_accumulation\_steps: 16
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 4 ### Training results ### Framework versions


* Transformers 4.27.0.dev0
* Pytorch 1.13.0
* Datasets 2.1.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #m2m_100 #text2text-generation #generated_from_trainer #dataset-squad #license-cc-by-nc-4.0 #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0001
* train\_batch\_size: 2
* eval\_batch\_size: 2
* seed: 42
* gradient\_accumulation\_steps: 16
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 4### Training results### Framework versions


* Transformers 4.27.0.dev0
* Pytorch 1.13.0
* Datasets 2.1.0
* Tokenizers 0.13.2