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speller-t5-8

Text2Text Generation
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PyTorch
TensorBoard
t5
Generated from Trainer
text-generation-inference
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@@ -15,12 +15,12 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [sberbank-ai/ruT5-base](https://huggingface.co/sberbank-ai/ruT5-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1580
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- - Rouge1: 28.0246
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- - Rouge2: 14.6131
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- - Rougel: 28.0357
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- - Rougelsum: 28.1585
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- - Gen Len: 41.6429
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  ## Model description
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@@ -50,35 +50,35 @@ The following hyperparameters were used during training:
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
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- |:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
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- | 1.0444 | 0.04 | 500 | 0.5084 | 23.8669 | 11.0011 | 23.8074 | 23.9137 | 48.2589 |
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- | 0.9248 | 0.07 | 1000 | 0.3787 | 27.1237 | 13.047 | 27.128 | 27.286 | 44.6518 |
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- | 0.6515 | 0.11 | 1500 | 0.3261 | 26.7152 | 12.8472 | 26.7857 | 27.0912 | 44.6429 |
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- | 0.5533 | 0.14 | 2000 | 0.2929 | 27.5391 | 13.497 | 27.5056 | 27.7679 | 42.2232 |
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- | 0.5962 | 0.18 | 2500 | 0.2678 | 27.2948 | 13.5317 | 27.3026 | 27.4828 | 42.7411 |
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- | 0.5667 | 0.22 | 3000 | 0.2549 | 27.4315 | 13.7922 | 27.4858 | 27.6141 | 42.5 |
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- | 0.4532 | 0.25 | 3500 | 0.2460 | 28.0246 | 14.6131 | 28.0357 | 28.1585 | 42.3929 |
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- | 0.4552 | 0.29 | 4000 | 0.2320 | 27.5 | 13.9435 | 27.567 | 27.6953 | 42.1161 |
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- | 0.4245 | 0.32 | 4500 | 0.2264 | 27.3214 | 13.3333 | 27.3884 | 27.5502 | 42.1607 |
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- | 0.4109 | 0.36 | 5000 | 0.2182 | 27.5 | 13.9435 | 27.567 | 27.6953 | 42.2411 |
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- | 0.3826 | 0.4 | 5500 | 0.2115 | 27.5 | 13.9435 | 27.567 | 27.6953 | 41.9196 |
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- | 0.4112 | 0.43 | 6000 | 0.2066 | 27.5 | 13.9435 | 27.567 | 27.6953 | 41.9018 |
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- | 0.4006 | 0.47 | 6500 | 0.1980 | 28.0246 | 14.6131 | 28.0357 | 28.1585 | 41.8304 |
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- | 0.3494 | 0.5 | 7000 | 0.1944 | 27.5 | 13.9435 | 27.567 | 27.6953 | 41.9554 |
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- | 0.3225 | 0.54 | 7500 | 0.1928 | 27.5 | 13.9435 | 27.567 | 27.6953 | 41.8929 |
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- | 0.3525 | 0.58 | 8000 | 0.1869 | 27.5 | 13.9435 | 27.567 | 27.6953 | 41.6071 |
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- | 0.3828 | 0.61 | 8500 | 0.1821 | 27.5 | 13.9435 | 27.567 | 27.6953 | 41.5446 |
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- | 0.3287 | 0.65 | 9000 | 0.1781 | 27.5 | 13.9435 | 27.567 | 27.6953 | 41.5714 |
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- | 0.3276 | 0.68 | 9500 | 0.1778 | 27.5 | 13.9435 | 27.567 | 27.6953 | 41.6786 |
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- | 0.3054 | 0.72 | 10000 | 0.1727 | 27.5 | 13.9435 | 27.567 | 27.6953 | 41.4375 |
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- | 0.3685 | 0.76 | 10500 | 0.1728 | 27.5 | 13.9435 | 27.567 | 27.6953 | 41.6964 |
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- | 0.3454 | 0.79 | 11000 | 0.1700 | 27.5 | 13.9435 | 27.567 | 27.6953 | 41.75 |
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- | 0.3056 | 0.83 | 11500 | 0.1641 | 27.5 | 13.9435 | 27.567 | 27.6953 | 41.7143 |
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- | 0.3399 | 0.86 | 12000 | 0.1606 | 27.5 | 13.9435 | 27.567 | 27.6953 | 41.7143 |
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- | 0.3079 | 0.9 | 12500 | 0.1600 | 27.5 | 13.9435 | 27.567 | 27.6953 | 41.6429 |
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- | 0.2646 | 0.94 | 13000 | 0.1591 | 28.0246 | 14.6131 | 28.0357 | 28.1585 | 41.5446 |
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- | 0.2297 | 0.97 | 13500 | 0.1580 | 28.0246 | 14.6131 | 28.0357 | 28.1585 | 41.6429 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [sberbank-ai/ruT5-base](https://huggingface.co/sberbank-ai/ruT5-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.1626
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+ - Rouge1: 14.5345
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+ - Rouge2: 9.6847
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+ - Rougel: 14.4144
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+ - Rougelsum: 14.3544
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+ - Gen Len: 37.7748
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  ## Model description
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
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+ |:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
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+ | 0.9929 | 0.04 | 500 | 0.5644 | 12.8915 | 6.982 | 12.7499 | 12.6126 | 39.3604 |
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+ | 1.2778 | 0.07 | 1000 | 0.4272 | 13.8323 | 8.1081 | 13.7538 | 13.6059 | 38.8288 |
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+ | 0.6384 | 0.11 | 1500 | 0.3654 | 14.1341 | 8.5586 | 14.034 | 13.9139 | 38.4865 |
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+ | 0.5993 | 0.15 | 2000 | 0.3318 | 14.009 | 8.3655 | 13.9339 | 13.7688 | 38.8018 |
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+ | 0.5327 | 0.18 | 2500 | 0.2969 | 14.2342 | 8.7838 | 14.1141 | 13.9339 | 37.7928 |
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+ | 0.4831 | 0.22 | 3000 | 0.2761 | 14.5345 | 9.6847 | 14.4144 | 14.3544 | 38.9369 |
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+ | 0.4582 | 0.25 | 3500 | 0.2562 | 14.5345 | 9.6847 | 14.4144 | 14.3544 | 39.2162 |
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+ | 0.3983 | 0.29 | 4000 | 0.2449 | 14.5345 | 9.6847 | 14.4144 | 14.3544 | 38.9459 |
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+ | 0.4459 | 0.33 | 4500 | 0.2422 | 14.4717 | 9.5045 | 14.4144 | 14.2206 | 38.8378 |
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+ | 0.4073 | 0.36 | 5000 | 0.2375 | 14.5345 | 9.6847 | 14.4144 | 14.3544 | 38.3964 |
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+ | 0.4047 | 0.4 | 5500 | 0.2263 | 14.5345 | 9.6847 | 14.4144 | 14.3544 | 39.2703 |
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+ | 0.3423 | 0.44 | 6000 | 0.2208 | 14.5345 | 9.6847 | 14.4144 | 14.3544 | 38.5405 |
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+ | 0.3348 | 0.47 | 6500 | 0.2109 | 14.5345 | 9.6847 | 14.4144 | 14.3544 | 37.7568 |
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+ | 0.3421 | 0.51 | 7000 | 0.2053 | 14.5345 | 9.6847 | 14.4144 | 14.3544 | 37.7117 |
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+ | 0.3319 | 0.54 | 7500 | 0.2025 | 14.2342 | 8.7838 | 14.1141 | 14.0541 | 37.5586 |
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+ | 0.3239 | 0.58 | 8000 | 0.1991 | 14.2342 | 8.7838 | 14.1141 | 14.0541 | 38.0541 |
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+ | 0.2963 | 0.62 | 8500 | 0.1959 | 14.2342 | 8.7838 | 14.1141 | 14.0541 | 38.0 |
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+ | 0.3117 | 0.65 | 9000 | 0.1899 | 14.2342 | 8.7838 | 14.1141 | 14.0541 | 37.7117 |
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+ | 0.2737 | 0.69 | 9500 | 0.1898 | 14.2342 | 8.7838 | 14.1141 | 14.0541 | 37.5135 |
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+ | 0.3425 | 0.73 | 10000 | 0.1830 | 14.2342 | 8.7838 | 14.1141 | 14.0541 | 37.6306 |
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+ | 0.2986 | 0.76 | 10500 | 0.1831 | 14.5345 | 9.6847 | 14.4144 | 14.3544 | 37.7658 |
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+ | 0.3312 | 0.8 | 11000 | 0.1734 | 14.2342 | 8.7838 | 14.1141 | 14.0541 | 37.973 |
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+ | 0.3461 | 0.83 | 11500 | 0.1753 | 14.5345 | 9.6847 | 14.4144 | 14.3544 | 37.6847 |
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+ | 0.2786 | 0.87 | 12000 | 0.1740 | 14.5345 | 9.6847 | 14.4144 | 14.3544 | 37.7748 |
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+ | 0.2911 | 0.91 | 12500 | 0.1672 | 14.5345 | 9.6847 | 14.4144 | 14.3544 | 37.7387 |
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+ | 0.2618 | 0.94 | 13000 | 0.1691 | 14.5345 | 9.6847 | 14.4144 | 14.3544 | 37.5135 |
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+ | 0.2844 | 0.98 | 13500 | 0.1626 | 14.5345 | 9.6847 | 14.4144 | 14.3544 | 37.7748 |
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  ### Framework versions