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raptorkwok
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cantonese-chinese-translation

Translation
Transformers
PyTorch
bart
text2text-generation
Generated from Trainer
Inference Endpoints
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update model card README.md

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@@ -15,10 +15,10 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [fnlp/bart-base-chinese](https://huggingface.co/fnlp/bart-base-chinese) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.2373
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- - Bleu: 58.9213
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- - Chrf: 57.6665
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- - Gen Len: 12.8396
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  ## Model description
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@@ -50,13 +50,15 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Bleu | Chrf | Gen Len |
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  |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|
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- | 0.3565 | 0.48 | 1000 | 0.2624 | 58.3152 | 56.9278 | 12.8539 |
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- | 0.3077 | 0.96 | 2000 | 0.2403 | 58.4429 | 57.226 | 12.8036 |
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- | 0.2297 | 1.44 | 3000 | 0.2469 | 58.6654 | 57.3437 | 12.8374 |
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- | 0.2256 | 1.92 | 4000 | 0.2373 | 58.9213 | 57.6665 | 12.8396 |
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- | 0.1711 | 2.39 | 5000 | 0.2427 | 58.8291 | 57.4604 | 12.8506 |
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- | 0.1694 | 2.87 | 6000 | 0.2500 | 58.4154 | 57.0752 | 12.813 |
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- | 0.1336 | 3.35 | 7000 | 0.2575 | 58.4311 | 57.0237 | 12.8415 |
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [fnlp/bart-base-chinese](https://huggingface.co/fnlp/bart-base-chinese) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.2258
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+ - Bleu: 62.1085
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+ - Chrf: 60.1854
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+ - Gen Len: 12.8755
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Bleu | Chrf | Gen Len |
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  |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|
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+ | 0.3606 | 0.48 | 1000 | 0.2592 | 60.9844 | 58.8851 | 12.8446 |
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+ | 0.3059 | 0.96 | 2000 | 0.2291 | 61.9606 | 60.1201 | 12.8621 |
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+ | 0.2296 | 1.44 | 3000 | 0.2254 | 61.9458 | 60.0434 | 12.8578 |
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+ | 0.2231 | 1.92 | 4000 | 0.2176 | 61.9617 | 59.9299 | 12.8827 |
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+ | 0.174 | 2.39 | 5000 | 0.2290 | 61.9661 | 59.8844 | 12.9068 |
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+ | 0.171 | 2.87 | 6000 | 0.2258 | 62.1085 | 60.1854 | 12.8755 |
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+ | 0.1346 | 3.35 | 7000 | 0.2334 | 61.4554 | 59.5055 | 12.8175 |
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+ | 0.1285 | 3.83 | 8000 | 0.2408 | 61.3332 | 59.3276 | 12.8412 |
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+ | 0.1061 | 4.31 | 9000 | 0.2530 | 61.6505 | 59.614 | 12.8566 |
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  ### Framework versions