pytorch marian text2text-generation transformers generated_from_trainer license:apache-2.0 model-index autotrain_compatible
---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: MIX2_en-ja_helsinki
  results: []
---

<!-- 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. -->

# MIX2_en-ja_helsinki

This model is a fine-tuned version of [Helsinki-NLP/opus-mt-en-jap](https://huggingface.co/Helsinki-NLP/opus-mt-en-jap) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6703

## 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: 0.0003
- train_batch_size: 96
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step   | Validation Loss |
|:-------------:|:-----:|:------:|:---------------:|
| 3.5357        | 0.02  | 4000   | 2.9519          |
| 2.8601        | 0.04  | 8000   | 2.6962          |
| 2.6183        | 0.06  | 12000  | 2.5156          |
| 2.4731        | 0.08  | 16000  | 2.4312          |
| 2.3731        | 0.1   | 20000  | 2.3575          |
| 2.2964        | 0.11  | 24000  | 2.3319          |
| 2.238         | 0.13  | 28000  | 2.2802          |
| 2.1919        | 0.15  | 32000  | 2.2552          |
| 2.1479        | 0.17  | 36000  | 2.2354          |
| 2.1104        | 0.19  | 40000  | 2.2210          |
| 2.0788        | 0.21  | 44000  | 2.1835          |
| 2.0552        | 0.23  | 48000  | 2.1391          |
| 2.0228        | 0.25  | 52000  | 2.1338          |
| 2.0062        | 0.27  | 56000  | 2.1115          |
| 1.9868        | 0.29  | 60000  | 2.1025          |
| 1.9628        | 0.31  | 64000  | 2.1334          |
| 1.9474        | 0.32  | 68000  | 2.0935          |
| 1.9318        | 0.34  | 72000  | 2.1030          |
| 1.9187        | 0.36  | 76000  | 2.0605          |
| 1.9019        | 0.38  | 80000  | 2.0388          |
| 1.8916        | 0.4   | 84000  | 2.0360          |
| 1.8775        | 0.42  | 88000  | 2.0356          |
| 1.8689        | 0.44  | 92000  | 2.0315          |
| 1.8558        | 0.46  | 96000  | 2.0169          |
| 1.8431        | 0.48  | 100000 | 2.0213          |
| 1.8373        | 0.5   | 104000 | 2.0071          |
| 1.8224        | 0.52  | 108000 | 2.0093          |
| 1.8181        | 0.53  | 112000 | 1.9952          |
| 1.8087        | 0.55  | 116000 | 1.9927          |
| 1.7998        | 0.57  | 120000 | 1.9726          |
| 1.7947        | 0.59  | 124000 | 1.9817          |
| 1.7874        | 0.61  | 128000 | 1.9650          |
| 1.7781        | 0.63  | 132000 | 1.9688          |
| 1.7712        | 0.65  | 136000 | 1.9655          |
| 1.7631        | 0.67  | 140000 | 1.9561          |
| 1.7577        | 0.69  | 144000 | 1.9529          |
| 1.7528        | 0.71  | 148000 | 1.9447          |
| 1.746         | 0.73  | 152000 | 1.9700          |
| 1.7386        | 0.74  | 156000 | 1.9413          |
| 1.7329        | 0.76  | 160000 | 1.9329          |
| 1.7285        | 0.78  | 164000 | 1.9289          |
| 1.7227        | 0.8   | 168000 | 1.9337          |
| 1.7186        | 0.82  | 172000 | 1.9263          |
| 1.7116        | 0.84  | 176000 | 1.9407          |
| 1.7072        | 0.86  | 180000 | 1.9059          |
| 1.7032        | 0.88  | 184000 | 1.9380          |
| 1.6932        | 0.9   | 188000 | 1.9183          |
| 1.6921        | 0.92  | 192000 | 1.9131          |
| 1.6875        | 0.94  | 196000 | 1.9180          |
| 1.6846        | 0.96  | 200000 | 1.9040          |
| 1.6797        | 0.97  | 204000 | 1.9089          |
| 1.6725        | 0.99  | 208000 | 1.9024          |
| 1.6589        | 1.01  | 212000 | 1.8909          |
| 1.6507        | 1.03  | 216000 | 1.8837          |
| 1.6441        | 1.05  | 220000 | 1.8906          |
| 1.6445        | 1.07  | 224000 | 1.8914          |
| 1.6394        | 1.09  | 228000 | 1.8833          |
| 1.6382        | 1.11  | 232000 | 1.8837          |
| 1.6376        | 1.13  | 236000 | 1.8869          |
| 1.6329        | 1.15  | 240000 | 1.8829          |
| 1.6294        | 1.17  | 244000 | 1.8845          |
| 1.6273        | 1.18  | 248000 | 1.8888          |
| 1.6243        | 1.2   | 252000 | 1.8709          |
| 1.6226        | 1.22  | 256000 | 1.8418          |
| 1.6177        | 1.24  | 260000 | 1.8587          |
| 1.6151        | 1.26  | 264000 | 1.8526          |
| 1.6111        | 1.28  | 268000 | 1.8494          |
| 1.6084        | 1.3   | 272000 | 1.8781          |
| 1.6043        | 1.32  | 276000 | 1.8390          |
| 1.6011        | 1.34  | 280000 | 1.8603          |
| 1.5999        | 1.36  | 284000 | 1.8515          |
| 1.5954        | 1.38  | 288000 | 1.8356          |
| 1.5936        | 1.39  | 292000 | 1.8530          |
| 1.5916        | 1.41  | 296000 | 1.8475          |
| 1.5886        | 1.43  | 300000 | 1.8410          |
| 1.5883        | 1.45  | 304000 | 1.8153          |
| 1.5828        | 1.47  | 308000 | 1.8254          |
| 1.582         | 1.49  | 312000 | 1.8139          |
| 1.578         | 1.51  | 316000 | 1.8366          |
| 1.5723        | 1.53  | 320000 | 1.8353          |
| 1.5705        | 1.55  | 324000 | 1.8230          |
| 1.5691        | 1.57  | 328000 | 1.8194          |
| 1.5656        | 1.59  | 332000 | 1.8069          |
| 1.566         | 1.6   | 336000 | 1.8204          |
| 1.5604        | 1.62  | 340000 | 1.8307          |
| 1.5573        | 1.64  | 344000 | 1.8209          |
| 1.5547        | 1.66  | 348000 | 1.8320          |
| 1.5545        | 1.68  | 352000 | 1.8179          |
| 1.5519        | 1.7   | 356000 | 1.8323          |
| 1.545         | 1.72  | 360000 | 1.8005          |
| 1.5483        | 1.74  | 364000 | 1.8034          |
| 1.5454        | 1.76  | 368000 | 1.7997          |
| 1.5393        | 1.78  | 372000 | 1.8078          |
| 1.5381        | 1.8   | 376000 | 1.8204          |
| 1.5347        | 1.81  | 380000 | 1.8071          |
| 1.5327        | 1.83  | 384000 | 1.7997          |
| 1.529         | 1.85  | 388000 | 1.8012          |
| 1.5287        | 1.87  | 392000 | 1.8028          |
| 1.5273        | 1.89  | 396000 | 1.8103          |
| 1.5194        | 1.91  | 400000 | 1.8008          |
| 1.5197        | 1.93  | 404000 | 1.8004          |
| 1.5218        | 1.95  | 408000 | 1.8024          |
| 1.514         | 1.97  | 412000 | 1.7852          |
| 1.5146        | 1.99  | 416000 | 1.7908          |
| 1.5045        | 2.01  | 420000 | 1.7864          |
| 1.4876        | 2.02  | 424000 | 1.7813          |
| 1.4846        | 2.04  | 428000 | 1.7822          |
| 1.4865        | 2.06  | 432000 | 1.7737          |
| 1.4857        | 2.08  | 436000 | 1.7668          |
| 1.4825        | 2.1   | 440000 | 1.7681          |
| 1.4828        | 2.12  | 444000 | 1.7685          |
| 1.4821        | 2.14  | 448000 | 1.7636          |
| 1.4778        | 2.16  | 452000 | 1.7778          |
| 1.4803        | 2.18  | 456000 | 1.7834          |
| 1.4766        | 2.2   | 460000 | 1.7801          |
| 1.4741        | 2.22  | 464000 | 1.7601          |
| 1.4705        | 2.23  | 468000 | 1.7665          |
| 1.4739        | 2.25  | 472000 | 1.7604          |
| 1.4694        | 2.27  | 476000 | 1.7803          |
| 1.4665        | 2.29  | 480000 | 1.7835          |
| 1.4668        | 2.31  | 484000 | 1.7670          |
| 1.4605        | 2.33  | 488000 | 1.7629          |
| 1.4626        | 2.35  | 492000 | 1.7612          |
| 1.4627        | 2.37  | 496000 | 1.7612          |
| 1.4569        | 2.39  | 500000 | 1.7557          |
| 1.455         | 2.41  | 504000 | 1.7599          |
| 1.4547        | 2.43  | 508000 | 1.7569          |
| 1.453         | 2.44  | 512000 | 1.7589          |
| 1.4515        | 2.46  | 516000 | 1.7679          |
| 1.4501        | 2.48  | 520000 | 1.7574          |
| 1.4446        | 2.5   | 524000 | 1.7526          |
| 1.4456        | 2.52  | 528000 | 1.7506          |
| 1.4445        | 2.54  | 532000 | 1.7484          |
| 1.4428        | 2.56  | 536000 | 1.7447          |
| 1.439         | 2.58  | 540000 | 1.7468          |
| 1.441         | 2.6   | 544000 | 1.7609          |
| 1.4358        | 2.62  | 548000 | 1.7498          |
| 1.4318        | 2.64  | 552000 | 1.7592          |
| 1.4276        | 2.65  | 556000 | 1.7452          |
| 1.4317        | 2.67  | 560000 | 1.7500          |
| 1.4277        | 2.69  | 564000 | 1.7392          |
| 1.4259        | 2.71  | 568000 | 1.7351          |
| 1.4239        | 2.73  | 572000 | 1.7385          |
| 1.4191        | 2.75  | 576000 | 1.7487          |
| 1.4204        | 2.77  | 580000 | 1.7392          |
| 1.4176        | 2.79  | 584000 | 1.7372          |
| 1.4147        | 2.81  | 588000 | 1.7347          |
| 1.4154        | 2.83  | 592000 | 1.7085          |
| 1.4134        | 2.85  | 596000 | 1.7103          |
| 1.4091        | 2.87  | 600000 | 1.7124          |
| 1.4091        | 2.88  | 604000 | 1.7369          |
| 1.406         | 2.9   | 608000 | 1.7142          |
| 1.4028        | 2.92  | 612000 | 1.7376          |
| 1.4019        | 2.94  | 616000 | 1.7201          |
| 1.4018        | 2.96  | 620000 | 1.7230          |
| 1.3959        | 2.98  | 624000 | 1.7206          |
| 1.3985        | 3.0   | 628000 | 1.7183          |
| 1.3681        | 3.02  | 632000 | 1.7283          |
| 1.3668        | 3.04  | 636000 | 1.7330          |
| 1.3687        | 3.06  | 640000 | 1.7187          |
| 1.3681        | 3.08  | 644000 | 1.7163          |
| 1.3687        | 3.09  | 648000 | 1.7249          |
| 1.364         | 3.11  | 652000 | 1.7283          |
| 1.364         | 3.13  | 656000 | 1.7091          |
| 1.3652        | 3.15  | 660000 | 1.7030          |
| 1.3623        | 3.17  | 664000 | 1.7058          |
| 1.3604        | 3.19  | 668000 | 1.7101          |
| 1.3598        | 3.21  | 672000 | 1.7104          |
| 1.3577        | 3.23  | 676000 | 1.7028          |
| 1.3574        | 3.25  | 680000 | 1.7023          |
| 1.3546        | 3.27  | 684000 | 1.7197          |
| 1.3549        | 3.29  | 688000 | 1.7045          |
| 1.3534        | 3.3   | 692000 | 1.6990          |
| 1.3511        | 3.32  | 696000 | 1.6971          |
| 1.3504        | 3.34  | 700000 | 1.6894          |
| 1.346         | 3.36  | 704000 | 1.6820          |
| 1.3467        | 3.38  | 708000 | 1.6920          |
| 1.3461        | 3.4   | 712000 | 1.6897          |
| 1.3425        | 3.42  | 716000 | 1.6962          |
| 1.34          | 3.44  | 720000 | 1.6864          |
| 1.3408        | 3.46  | 724000 | 1.6860          |
| 1.3387        | 3.48  | 728000 | 1.6924          |
| 1.3377        | 3.5   | 732000 | 1.6919          |
| 1.3378        | 3.51  | 736000 | 1.6858          |
| 1.334         | 3.53  | 740000 | 1.6816          |
| 1.3347        | 3.55  | 744000 | 1.6867          |
| 1.3307        | 3.57  | 748000 | 1.6859          |
| 1.3316        | 3.59  | 752000 | 1.6896          |
| 1.3257        | 3.61  | 756000 | 1.6824          |
| 1.3222        | 3.63  | 760000 | 1.6819          |
| 1.3247        | 3.65  | 764000 | 1.6809          |
| 1.3207        | 3.67  | 768000 | 1.6775          |
| 1.3227        | 3.69  | 772000 | 1.6807          |
| 1.3203        | 3.71  | 776000 | 1.6750          |
| 1.3203        | 3.72  | 780000 | 1.6758          |
| 1.316         | 3.74  | 784000 | 1.6787          |
| 1.3147        | 3.76  | 788000 | 1.6747          |
| 1.3146        | 3.78  | 792000 | 1.6718          |
| 1.3137        | 3.8   | 796000 | 1.6744          |
| 1.3143        | 3.82  | 800000 | 1.6733          |
| 1.3123        | 3.84  | 804000 | 1.6754          |
| 1.3069        | 3.86  | 808000 | 1.6734          |
| 1.3122        | 3.88  | 812000 | 1.6742          |
| 1.3074        | 3.9   | 816000 | 1.6742          |
| 1.3006        | 3.92  | 820000 | 1.6709          |
| 1.308         | 3.93  | 824000 | 1.6714          |
| 1.3063        | 3.95  | 828000 | 1.6727          |
| 1.3036        | 3.97  | 832000 | 1.6711          |
| 1.3048        | 3.99  | 836000 | 1.6703          |


### Framework versions

- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1
