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# greek-nllb-4ep-512

This model is a fine-tuned version of [facebook/nllb-200-distilled-600M](https://huggingface.co/facebook/nllb-200-distilled-600M) on the squad_modified_for_t5_qg_2 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2852

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 2.2208        | 0.17  | 100  | 1.5566          |
| 1.7198        | 0.34  | 200  | 1.4767          |
| 1.5435        | 0.51  | 300  | 1.4467          |
| 1.5017        | 0.67  | 400  | 1.3955          |
| 1.4569        | 0.84  | 500  | 1.3711          |
| 1.4496        | 1.01  | 600  | 1.3556          |
| 1.3174        | 1.18  | 700  | 1.3488          |
| 1.3025        | 1.35  | 800  | 1.3398          |
| 1.3013        | 1.52  | 900  | 1.3286          |
| 1.2938        | 1.69  | 1000 | 1.3161          |
| 1.2984        | 1.86  | 1100 | 1.3057          |
| 1.2494        | 2.03  | 1200 | 1.3097          |
| 1.1843        | 2.2   | 1300 | 1.2985          |
| 1.1868        | 2.36  | 1400 | 1.3021          |
| 1.1875        | 2.53  | 1500 | 1.2958          |
| 1.1854        | 2.7   | 1600 | 1.2987          |
| 1.1818        | 2.87  | 1700 | 1.2885          |
| 1.1696        | 3.04  | 1800 | 1.2912          |
| 1.1108        | 3.21  | 1900 | 1.2880          |
| 1.1301        | 3.38  | 2000 | 1.2889          |
| 1.1139        | 3.55  | 2100 | 1.2869          |
| 1.1098        | 3.72  | 2200 | 1.2879          |
| 1.1073        | 3.88  | 2300 | 1.2852          |


### Framework versions

- Transformers 4.27.0.dev0
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2

{"license": "cc-by-nc-4.0", "tags": ["generated_from_trainer"], "datasets": ["squad_modified_for_t5_qg_2"], "model-index": [{"name": "greek-nllb-4ep-512", "results": []}]}
transformers pytorch m2m_100 text2text-generation generated_from_trainer dataset:squad_modified_for_t5_qg_2 license:cc-by-nc-4.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #m2m_100 #text2text-generation #generated_from_trainer #dataset-squad_modified_for_t5_qg_2 #license-cc-by-nc-4.0 #autotrain_compatible #endpoints_compatible #region-us 

greek-nllb-4ep-512
==================


This model is a fine-tuned version of facebook/nllb-200-distilled-600M on the squad\_modified\_for\_t5\_qg\_2 dataset.
It achieves the following results on the evaluation set:


* Loss: 1.2852


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 1.13.1+cu116
* Datasets 2.10.1
* 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 1.13.1+cu116
* Datasets 2.10.1
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #m2m_100 #text2text-generation #generated_from_trainer #dataset-squad_modified_for_t5_qg_2 #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 1.13.1+cu116
* Datasets 2.10.1
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #m2m_100 #text2text-generation #generated_from_trainer #dataset-squad_modified_for_t5_qg_2 #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 1.13.1+cu116
* Datasets 2.10.1
* Tokenizers 0.13.2