
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# es_fi_all_copy_quy

This model is a fine-tuned version of [Helsinki-NLP/opus-mt-es-fi](https://huggingface.co/Helsinki-NLP/opus-mt-es-fi) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4826
- Bleu: 1.0774
- Chrf: 27.8374
- Gen Len: 49.2425

## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Bleu   | Chrf    | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:-------:|:-------:|
| 0.5479        | 0.03  | 1000  | 0.6737          | 0.3055 | 13.5765 | 61.5895 |
| 0.4856        | 0.07  | 2000  | 0.6330          | 0.1975 | 16.9698 | 73.9869 |
| 0.4541        | 0.1   | 3000  | 0.6120          | 0.1727 | 17.4235 | 77.335  |
| 0.4381        | 0.13  | 4000  | 0.5962          | 0.3781 | 18.0872 | 48.1066 |
| 0.4236        | 0.17  | 5000  | 0.5880          | 0.3741 | 18.808  | 60.0463 |
| 0.4165        | 0.2   | 6000  | 0.5721          | 0.4366 | 19.5753 | 54.2746 |
| 0.3978        | 0.23  | 7000  | 0.5669          | 0.3667 | 20.4865 | 57.9366 |
| 0.3916        | 0.27  | 8000  | 0.5536          | 0.8014 | 21.485  | 47.503  |
| 0.3747        | 0.3   | 9000  | 0.5501          | 0.5344 | 21.0513 | 60.3924 |
| 0.3825        | 0.33  | 10000 | 0.5375          | 0.4356 | 22.2798 | 56.7726 |
| 0.3716        | 0.36  | 11000 | 0.5390          | 0.5945 | 23.2025 | 53.9366 |
| 0.3518        | 0.4   | 12000 | 0.5312          | 0.7343 | 23.1143 | 52.326  |
| 0.3495        | 0.43  | 13000 | 0.5217          | 1.0112 | 24.6907 | 49.3903 |
| 0.3508        | 0.46  | 14000 | 0.5222          | 0.5915 | 23.556  | 57.2656 |
| 0.3464        | 0.5   | 15000 | 0.5165          | 0.7044 | 24.2944 | 59.159  |
| 0.3476        | 0.53  | 16000 | 0.5142          | 1.1    | 25.0408 | 52.1127 |
| 0.3444        | 0.56  | 17000 | 0.5108          | 0.9361 | 24.8808 | 48.9366 |
| 0.3404        | 0.6   | 18000 | 0.5056          | 0.9007 | 25.3524 | 51.6962 |
| 0.3286        | 0.63  | 19000 | 0.5029          | 0.9896 | 24.8249 | 52.7233 |
| 0.3362        | 0.66  | 20000 | 0.5012          | 0.8774 | 26.6471 | 47.3732 |
| 0.3386        | 0.7   | 21000 | 0.5028          | 0.8963 | 25.7596 | 54.1861 |
| 0.3371        | 0.73  | 22000 | 0.5002          | 0.8477 | 24.9775 | 54.2958 |
| 0.3284        | 0.76  | 23000 | 0.4955          | 0.9197 | 25.5964 | 55.2606 |
| 0.3239        | 0.8   | 24000 | 0.4943          | 1.1353 | 27.5912 | 48.5714 |
| 0.3214        | 0.83  | 25000 | 0.4889          | 0.9846 | 26.098  | 51.0221 |
| 0.3183        | 0.86  | 26000 | 0.4889          | 1.1816 | 28.4223 | 44.1288 |
| 0.3164        | 0.89  | 27000 | 0.4874          | 1.028  | 27.4202 | 48.2616 |
| 0.3162        | 0.93  | 28000 | 0.4839          | 1.0008 | 26.1891 | 54.4095 |
| 0.3167        | 0.96  | 29000 | 0.4837          | 1.1952 | 27.7299 | 47.3159 |
| 0.3141        | 0.99  | 30000 | 0.4809          | 0.7488 | 27.6076 | 48.9638 |
| 0.3043        | 1.03  | 31000 | 0.4826          | 1.0774 | 27.8374 | 49.2425 |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu117
- Datasets 2.11.0
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["bleu"], "model-index": [{"name": "es_fi_all_copy_quy", "results": []}]}
transformers pytorch marian text2text-generation generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #marian #text2text-generation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

es\_fi\_all\_copy\_quy
======================


This model is a fine-tuned version of Helsinki-NLP/opus-mt-es-fi on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.4826
* Bleu: 1.0774
* Chrf: 27.8374
* Gen Len: 49.2425


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: 2e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu117
* Datasets 2.11.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu117
* Datasets 2.11.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #marian #text2text-generation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu117
* Datasets 2.11.0
* Tokenizers 0.13.3