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opus-mt-cantonese-v1

Text2Text Generation
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  1. README.md +64 -14
  2. model.safetensors +1 -1
  3. runs/Mar31_03-54-31_9106895eed54/events.out.tfevents.1711857279.9106895eed54.1341.3 +2 -2
README.md CHANGED
@@ -17,9 +17,9 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [Helsinki-NLP/opus-mt-en-zh](https://huggingface.co/Helsinki-NLP/opus-mt-en-zh) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 3.7154
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- - Bleu: 1.4102
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- - Gen Len: 12.6992
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  ## Model description
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@@ -44,23 +44,73 @@ The following hyperparameters were used during training:
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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- - num_epochs: 10
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  - mixed_precision_training: Native AMP
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|
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- | No log | 1.0 | 62 | 3.7154 | 1.3724 | 12.7073 |
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- | No log | 2.0 | 124 | 3.7185 | 1.3718 | 12.7398 |
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- | No log | 3.0 | 186 | 3.7168 | 1.4342 | 12.6504 |
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- | No log | 4.0 | 248 | 3.7168 | 1.4109 | 12.7805 |
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- | No log | 5.0 | 310 | 3.7161 | 1.4265 | 12.7073 |
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- | No log | 6.0 | 372 | 3.7150 | 1.4013 | 12.7114 |
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- | No log | 7.0 | 434 | 3.7151 | 1.4102 | 12.7073 |
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- | No log | 8.0 | 496 | 3.7152 | 1.3981 | 12.7439 |
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- | 2.0086 | 9.0 | 558 | 3.7152 | 1.4327 | 12.6951 |
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- | 2.0086 | 10.0 | 620 | 3.7154 | 1.4102 | 12.6992 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [Helsinki-NLP/opus-mt-en-zh](https://huggingface.co/Helsinki-NLP/opus-mt-en-zh) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 3.7970
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+ - Bleu: 1.5351
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+ - Gen Len: 12.6626
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  ## Model description
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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+ - num_epochs: 60
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  - mixed_precision_training: Native AMP
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|
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+ | No log | 1.0 | 62 | 3.7171 | 1.4013 | 12.6341 |
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+ | No log | 2.0 | 124 | 3.7238 | 1.4412 | 12.7154 |
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+ | No log | 3.0 | 186 | 3.7223 | 1.4767 | 12.6098 |
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+ | No log | 4.0 | 248 | 3.7239 | 1.4567 | 12.6585 |
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+ | No log | 5.0 | 310 | 3.7230 | 1.4797 | 12.6707 |
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+ | No log | 6.0 | 372 | 3.7228 | 1.4804 | 12.6585 |
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+ | No log | 7.0 | 434 | 3.7244 | 1.4968 | 12.5976 |
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+ | No log | 8.0 | 496 | 3.7268 | 1.4797 | 12.6057 |
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+ | 1.8247 | 9.0 | 558 | 3.7248 | 1.486 | 12.6911 |
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+ | 1.8247 | 10.0 | 620 | 3.7292 | 1.4833 | 12.6829 |
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+ | 1.8247 | 11.0 | 682 | 3.7276 | 1.4767 | 12.687 |
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+ | 1.8247 | 12.0 | 744 | 3.7321 | 1.454 | 12.8374 |
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+ | 1.8247 | 13.0 | 806 | 3.7357 | 1.467 | 12.8211 |
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+ | 1.8247 | 14.0 | 868 | 3.7373 | 1.4605 | 12.8171 |
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+ | 1.8247 | 15.0 | 930 | 3.7369 | 1.4793 | 12.748 |
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+ | 1.8247 | 16.0 | 992 | 3.7385 | 1.4626 | 12.8984 |
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+ | 1.6597 | 17.0 | 1054 | 3.7406 | 1.4831 | 12.8089 |
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+ | 1.6597 | 18.0 | 1116 | 3.7439 | 1.513 | 12.7846 |
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+ | 1.6597 | 19.0 | 1178 | 3.7423 | 1.514 | 12.6545 |
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+ | 1.6597 | 20.0 | 1240 | 3.7485 | 1.4928 | 12.8659 |
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+ | 1.6597 | 21.0 | 1302 | 3.7493 | 1.5506 | 12.7033 |
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+ | 1.6597 | 22.0 | 1364 | 3.7544 | 1.5185 | 12.7439 |
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+ | 1.6597 | 23.0 | 1426 | 3.7558 | 1.4922 | 12.8049 |
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+ | 1.6597 | 24.0 | 1488 | 3.7589 | 1.4803 | 12.7683 |
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+ | 1.5288 | 25.0 | 1550 | 3.7586 | 1.5488 | 12.7642 |
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+ | 1.5288 | 26.0 | 1612 | 3.7591 | 1.5345 | 12.748 |
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+ | 1.5288 | 27.0 | 1674 | 3.7615 | 1.5416 | 12.7805 |
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+ | 1.5288 | 28.0 | 1736 | 3.7646 | 1.5416 | 12.752 |
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+ | 1.5288 | 29.0 | 1798 | 3.7665 | 1.5377 | 12.7683 |
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+ | 1.5288 | 30.0 | 1860 | 3.7670 | 1.515 | 12.7561 |
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+ | 1.5288 | 31.0 | 1922 | 3.7680 | 1.515 | 12.7846 |
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+ | 1.5288 | 32.0 | 1984 | 3.7705 | 1.5181 | 12.7236 |
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+ | 1.425 | 33.0 | 2046 | 3.7717 | 1.502 | 12.7236 |
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+ | 1.425 | 34.0 | 2108 | 3.7741 | 1.5461 | 12.6992 |
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+ | 1.425 | 35.0 | 2170 | 3.7781 | 1.4945 | 12.7561 |
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+ | 1.425 | 36.0 | 2232 | 3.7790 | 1.5391 | 12.748 |
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+ | 1.425 | 37.0 | 2294 | 3.7818 | 1.5798 | 12.7154 |
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+ | 1.425 | 38.0 | 2356 | 3.7827 | 1.5653 | 12.7276 |
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+ | 1.425 | 39.0 | 2418 | 3.7833 | 1.525 | 12.7195 |
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+ | 1.425 | 40.0 | 2480 | 3.7853 | 1.522 | 12.752 |
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+ | 1.3476 | 41.0 | 2542 | 3.7875 | 1.522 | 12.7195 |
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+ | 1.3476 | 42.0 | 2604 | 3.7880 | 1.4983 | 12.7276 |
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+ | 1.3476 | 43.0 | 2666 | 3.7891 | 1.5532 | 12.752 |
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+ | 1.3476 | 44.0 | 2728 | 3.7896 | 1.5532 | 12.7398 |
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+ | 1.3476 | 45.0 | 2790 | 3.7915 | 1.5013 | 12.7439 |
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+ | 1.3476 | 46.0 | 2852 | 3.7933 | 1.5051 | 12.7358 |
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+ | 1.3476 | 47.0 | 2914 | 3.7921 | 1.5013 | 12.7195 |
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+ | 1.3476 | 48.0 | 2976 | 3.7922 | 1.5081 | 12.7073 |
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+ | 1.3068 | 49.0 | 3038 | 3.7928 | 1.5081 | 12.7033 |
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+ | 1.3068 | 50.0 | 3100 | 3.7935 | 1.5043 | 12.7073 |
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+ | 1.3068 | 51.0 | 3162 | 3.7939 | 1.5043 | 12.7073 |
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+ | 1.3068 | 52.0 | 3224 | 3.7951 | 1.5051 | 12.7154 |
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+ | 1.3068 | 53.0 | 3286 | 3.7947 | 1.5351 | 12.6707 |
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+ | 1.3068 | 54.0 | 3348 | 3.7951 | 1.5382 | 12.6667 |
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+ | 1.3068 | 55.0 | 3410 | 3.7954 | 1.5351 | 12.6748 |
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+ | 1.3068 | 56.0 | 3472 | 3.7958 | 1.5351 | 12.6748 |
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+ | 1.279 | 57.0 | 3534 | 3.7962 | 1.5281 | 12.6545 |
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+ | 1.279 | 58.0 | 3596 | 3.7967 | 1.5281 | 12.6545 |
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+ | 1.279 | 59.0 | 3658 | 3.7969 | 1.5351 | 12.6626 |
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+ | 1.279 | 60.0 | 3720 | 3.7970 | 1.5351 | 12.6626 |
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  ### Framework versions
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