transformers safetensors m2m_100 text2text-generation generated_from_trainer base_model:facebook/m2m100_1.2B license:mit autotrain_compatible endpoints_compatible region:us
---
license: mit
base_model: facebook/m2m100_1.2B
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: cs_m2m_0.0001_100_v0.2
  results: []
---

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# cs_m2m_0.0001_100_v0.2

This model is a fine-tuned version of [facebook/m2m100_1.2B](https://huggingface.co/facebook/m2m100_1.2B) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 8.4496
- Bleu: 0.0928
- Gen Len: 62.0

## 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: 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: 100

### Training results

| Training Loss | Epoch | Step | Validation Loss | Bleu   | Gen Len  |
|:-------------:|:-----:|:----:|:---------------:|:------:|:--------:|
| 3.1218        | 1.0   | 6    | 8.4336          | 0.0372 | 115.8571 |
| 1.7719        | 2.0   | 12   | 8.4226          | 0.0454 | 83.1429  |
| 2.2391        | 3.0   | 18   | 8.3857          | 0.0595 | 67.8571  |
| 3.3595        | 4.0   | 24   | 8.3587          | 0.117  | 59.1429  |
| 3.2809        | 5.0   | 30   | 8.3475          | 0.0806 | 70.4286  |
| 2.5704        | 6.0   | 36   | 8.3259          | 0.1683 | 69.8095  |
| 3.8725        | 7.0   | 42   | 8.3405          | 0.0339 | 109.9048 |
| 2.9887        | 8.0   | 48   | 8.3686          | 0.0447 | 91.1905  |
| 2.9363        | 9.0   | 54   | 8.3856          | 0.0547 | 80.5238  |
| 2.3718        | 10.0  | 60   | 8.3621          | 0.0594 | 66.619   |
| 2.977         | 11.0  | 66   | 8.3563          | 0.0356 | 107.1905 |
| 2.4379        | 12.0  | 72   | 8.3682          | 0.0266 | 150.619  |
| 1.9983        | 13.0  | 78   | 8.3733          | 0.0655 | 96.619   |
| 2.5183        | 14.0  | 84   | 8.3767          | 0.0417 | 92.1905  |
| 4.7446        | 15.0  | 90   | 8.3677          | 0.0457 | 81.1429  |
| 2.8195        | 16.0  | 96   | 8.3779          | 0.0467 | 81.381   |
| 3.1357        | 17.0  | 102  | 8.3751          | 0.0531 | 123.4762 |
| 3.1353        | 18.0  | 108  | 8.3707          | 0.1118 | 83.4286  |
| 2.2632        | 19.0  | 114  | 8.3813          | 0.1173 | 80.0476  |
| 1.7457        | 20.0  | 120  | 8.3786          | 0.1014 | 100.6667 |
| 1.991         | 21.0  | 126  | 8.3845          | 0.0937 | 60.381   |
| 3.1272        | 22.0  | 132  | 8.3823          | 0.0648 | 75.0     |
| 2.5017        | 23.0  | 138  | 8.3882          | 0.1951 | 41.7619  |
| 3.1988        | 24.0  | 144  | 8.3901          | 0.2921 | 17.381   |
| 2.0247        | 25.0  | 150  | 8.3950          | 0.0929 | 50.8095  |
| 2.8855        | 26.0  | 156  | 8.4009          | 0.1452 | 37.8095  |
| 1.8024        | 27.0  | 162  | 8.3844          | 0.0439 | 95.2381  |
| 4.727         | 28.0  | 168  | 8.3750          | 0.0352 | 106.8571 |
| 2.3243        | 29.0  | 174  | 8.3736          | 0.0344 | 123.619  |
| 2.4946        | 30.0  | 180  | 8.3908          | 0.1952 | 112.4286 |
| 3.2337        | 31.0  | 186  | 8.3960          | 0.2593 | 58.9048  |
| 3.1065        | 32.0  | 192  | 8.3937          | 0.3752 | 48.0952  |
| 3.3689        | 33.0  | 198  | 8.3855          | 0.3984 | 48.8571  |
| 2.51          | 34.0  | 204  | 8.3928          | 0.2597 | 53.7143  |
| 1.5195        | 35.0  | 210  | 8.3917          | 0.1361 | 74.7143  |
| 2.1133        | 36.0  | 216  | 8.3964          | 0.0702 | 78.4286  |
| 2.6349        | 37.0  | 222  | 8.3839          | 0.0477 | 103.4286 |
| 2.2733        | 38.0  | 228  | 8.3770          | 0.0746 | 77.381   |
| 3.0805        | 39.0  | 234  | 8.3773          | 0.1324 | 75.3333  |
| 3.1701        | 40.0  | 240  | 8.3853          | 0.0776 | 75.8571  |
| 2.5676        | 41.0  | 246  | 8.3988          | 0.1274 | 76.7619  |
| 5.1543        | 42.0  | 252  | 8.4117          | 0.0381 | 110.2857 |
| 2.4138        | 43.0  | 258  | 8.4101          | 0.0472 | 92.619   |
| 2.6           | 44.0  | 264  | 8.3991          | 0.0422 | 102.0    |
| 5.2608        | 45.0  | 270  | 8.3912          | 0.0602 | 84.4762  |
| 2.6492        | 46.0  | 276  | 8.3918          | 0.0667 | 80.6667  |
| 2.5329        | 47.0  | 282  | 8.3901          | 0.1159 | 42.2857  |
| 2.894         | 48.0  | 288  | 8.3936          | 0.1352 | 46.381   |
| 2.6136        | 49.0  | 294  | 8.3959          | 0.1059 | 45.4286  |
| 3.2249        | 50.0  | 300  | 8.3954          | 0.246  | 46.1429  |
| 2.8511        | 51.0  | 306  | 8.3923          | 0.1572 | 52.8571  |
| 2.7592        | 52.0  | 312  | 8.3875          | 0.1112 | 62.1429  |
| 2.37          | 53.0  | 318  | 8.3839          | 0.0926 | 67.3333  |
| 3.1555        | 54.0  | 324  | 8.3989          | 0.0855 | 71.2381  |
| 2.723         | 55.0  | 330  | 8.4030          | 0.0756 | 78.4286  |
| 2.498         | 56.0  | 336  | 8.4131          | 0.3874 | 74.9048  |
| 2.6088        | 57.0  | 342  | 8.4278          | 0.118  | 83.7143  |
| 2.1392        | 58.0  | 348  | 8.4388          | 0.3423 | 80.381   |
| 2.8988        | 59.0  | 354  | 8.4506          | 0.0844 | 73.9048  |
| 2.2013        | 60.0  | 360  | 8.4596          | 0.0892 | 70.1429  |
| 2.2335        | 61.0  | 366  | 8.4694          | 0.1165 | 59.4762  |
| 3.306         | 62.0  | 372  | 8.4838          | 0.1685 | 49.4762  |
| 3.0362        | 63.0  | 378  | 8.4894          | 0.1189 | 56.1905  |
| 3.0111        | 64.0  | 384  | 8.4909          | 0.0926 | 66.5714  |
| 2.802         | 65.0  | 390  | 8.4956          | 0.0906 | 66.0     |
| 2.4222        | 66.0  | 396  | 8.4917          | 0.0742 | 72.381   |
| 2.8748        | 67.0  | 402  | 8.4870          | 0.0704 | 76.0952  |
| 2.7946        | 68.0  | 408  | 8.4823          | 0.0572 | 84.2381  |
| 2.7195        | 69.0  | 414  | 8.4714          | 0.0573 | 84.2381  |
| 2.487         | 70.0  | 420  | 8.4640          | 0.0578 | 83.3333  |
| 1.5811        | 71.0  | 426  | 8.4632          | 0.0516 | 91.381   |
| 2.7705        | 72.0  | 432  | 8.4618          | 0.0597 | 80.619   |
| 2.3703        | 73.0  | 438  | 8.4622          | 0.0598 | 80.619   |
| 2.4037        | 74.0  | 444  | 8.4618          | 0.0906 | 66.2381  |
| 2.3173        | 75.0  | 450  | 8.4579          | 0.0926 | 63.381   |
| 1.8697        | 76.0  | 456  | 8.4564          | 0.0942 | 62.5238  |
| 1.8887        | 77.0  | 462  | 8.4554          | 0.0979 | 62.6667  |
| 3.84          | 78.0  | 468  | 8.4590          | 0.077  | 70.1429  |
| 2.388         | 79.0  | 474  | 8.4654          | 0.0735 | 71.2381  |
| 2.591         | 80.0  | 480  | 8.4685          | 0.075  | 70.9048  |
| 2.7345        | 81.0  | 486  | 8.4665          | 0.0791 | 52.5238  |
| 2.7887        | 82.0  | 492  | 8.4669          | 0.0759 | 70.2381  |
| 2.5452        | 83.0  | 498  | 8.4675          | 0.0764 | 70.8095  |
| 2.7554        | 84.0  | 504  | 8.4693          | 0.096  | 53.9524  |
| 4.2388        | 85.0  | 510  | 8.4656          | 0.0939 | 62.8571  |
| 2.361         | 86.0  | 516  | 8.4612          | 0.0923 | 63.9524  |
| 1.912         | 87.0  | 522  | 8.4569          | 0.0916 | 62.5714  |
| 2.2787        | 88.0  | 528  | 8.4524          | 0.0942 | 63.2857  |
| 1.9425        | 89.0  | 534  | 8.4530          | 0.0942 | 62.0952  |
| 2.7257        | 90.0  | 540  | 8.4545          | 0.0967 | 61.381   |
| 1.9149        | 91.0  | 546  | 8.4552          | 0.0959 | 61.8095  |
| 2.507         | 92.0  | 552  | 8.4546          | 0.0936 | 63.1429  |
| 2.8124        | 93.0  | 558  | 8.4547          | 0.0947 | 63.2857  |
| 2.3852        | 94.0  | 564  | 8.4527          | 0.0955 | 62.8571  |
| 1.7975        | 95.0  | 570  | 8.4528          | 0.0947 | 63.2857  |
| 4.9651        | 96.0  | 576  | 8.4517          | 0.0922 | 62.4286  |
| 2.1141        | 97.0  | 582  | 8.4510          | 0.0928 | 62.0     |
| 2.6156        | 98.0  | 588  | 8.4502          | 0.0928 | 62.0     |
| 1.987         | 99.0  | 594  | 8.4498          | 0.0928 | 62.0     |
| 2.5299        | 100.0 | 600  | 8.4496          | 0.0928 | 62.0     |


### Framework versions

- Transformers 4.35.2
- Pytorch 1.13.1+cu117
- Datasets 2.16.1
- Tokenizers 0.15.0
