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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: 1.2837

## 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.2156        | 0.17  | 100  | 1.5542          |
| 1.7147        | 0.34  | 200  | 1.4823          |
| 1.5438        | 0.51  | 300  | 1.4377          |
| 1.5006        | 0.67  | 400  | 1.3997          |
| 1.4573        | 0.84  | 500  | 1.3753          |
| 1.4484        | 1.01  | 600  | 1.3596          |
| 1.3177        | 1.18  | 700  | 1.3491          |
| 1.2981        | 1.35  | 800  | 1.3432          |
| 1.2977        | 1.52  | 900  | 1.3346          |
| 1.2898        | 1.69  | 1000 | 1.3183          |
| 1.2964        | 1.86  | 1100 | 1.3114          |
| 1.2480        | 2.03  | 1200 | 1.3176          |
| 1.1766        | 2.2   | 1300 | 1.3019          |
| 1.1779        | 2.36  | 1400 | 1.3076          |
| 1.1770        | 2.53  | 1500 | 1.2968          |
| 1.1793        | 2.7   | 1600 | 1.2967          |
| 1.1721        | 2.87  | 1700 | 1.2879          |
| 1.1593        | 3.04  | 1800 | 1.2964          |
| 1.0904        | 3.21  | 1900 | 1.2948          |
| 1.1110        | 3.38  | 2000 | 1.2885          |
| 1.0947        | 3.55  | 2100 | 1.2885          |
| 1.0936        | 3.72  | 2200 | 1.2872          |
| 1.0875        | 4.05  | 2300 | 1.2823          |
| 1.0875        | 4.22  | 2400 | 1.2904          |
| 1.0875        | 4.39  | 2500 | 1.2875          |
| 1.0875        | 4.56  | 2600 | 1.2888          |
| 1.0875        | 4.73  | 2700 | 1.2865          |
| 1.0875        | 4.89  | 2800 | 1.2861          |
| 1.0875        | 5.00  | 2900 | 1.2837          |


### 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-5ep-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: 1.2837


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: 5


### 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: 5 ### 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: 5 ### Training results ### Framework versions


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