alexue4 commited on
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End of training

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README.md CHANGED
@@ -15,7 +15,7 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0632
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  - Mean Distance: 0
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  - Max Distance: 1
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@@ -37,58 +37,38 @@ More information needed
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  The following hyperparameters were used during training:
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  - learning_rate: 0.0001
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- - train_batch_size: 15
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- - eval_batch_size: 15
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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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  - lr_scheduler_warmup_ratio: 0.1
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- - num_epochs: 40
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Mean Distance | Max Distance |
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- |:-------------:|:-----:|:------:|:---------------:|:-------------:|:------------:|
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- | 0.8541 | 1.0 | 2664 | 0.3404 | 0 | 1 |
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- | 0.0451 | 2.0 | 5328 | 0.0605 | 0 | 1 |
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- | 0.0112 | 3.0 | 7992 | 0.0411 | 0 | 1 |
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- | 0.0068 | 4.0 | 10656 | 0.0205 | 0 | 1 |
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- | 0.007 | 5.0 | 13320 | 0.0242 | 0 | 1 |
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- | 0.0022 | 6.0 | 15984 | 0.0272 | 0 | 1 |
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- | 0.0054 | 7.0 | 18648 | 0.0080 | 0 | 1 |
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- | 0.0036 | 8.0 | 21312 | 0.0252 | 0 | 1 |
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- | 0.0039 | 9.0 | 23976 | 0.0210 | 0 | 1 |
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- | 0.0026 | 10.0 | 26640 | 0.0170 | 0 | 1 |
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- | 0.0026 | 11.0 | 29304 | 0.0043 | 0 | 1 |
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- | 0.0029 | 12.0 | 31968 | 0.0135 | 0 | 1 |
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- | 0.0011 | 13.0 | 34632 | 0.0313 | 0 | 1 |
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- | 0.0017 | 14.0 | 37296 | 0.0353 | 0 | 1 |
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- | 0.0014 | 15.0 | 39960 | 0.0117 | 0 | 1 |
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- | 0.0014 | 16.0 | 42624 | 0.0140 | 0 | 1 |
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- | 0.0013 | 17.0 | 45288 | 0.0220 | 0 | 1 |
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- | 0.0009 | 18.0 | 47952 | 0.0247 | 0 | 1 |
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- | 0.0017 | 19.0 | 50616 | 0.0322 | 0 | 1 |
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- | 0.0022 | 20.0 | 53280 | 0.0314 | 0 | 1 |
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- | 0.0006 | 21.0 | 55944 | 0.0305 | 0 | 1 |
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- | 0.001 | 22.0 | 58608 | 0.0292 | 0 | 1 |
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- | 0.0008 | 23.0 | 61272 | 0.0373 | 0 | 1 |
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- | 0.0008 | 24.0 | 63936 | 0.0309 | 0 | 1 |
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- | 0.0008 | 25.0 | 66600 | 0.0385 | 0 | 1 |
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- | 0.0014 | 26.0 | 69264 | 0.0134 | 0 | 1 |
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- | 0.0004 | 27.0 | 71928 | 0.0239 | 0 | 1 |
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- | 0.0011 | 28.0 | 74592 | 0.0164 | 0 | 1 |
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- | 0.0002 | 29.0 | 77256 | 0.0186 | 0 | 1 |
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- | 0.0001 | 30.0 | 79920 | 0.0298 | 0 | 1 |
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- | 0.0008 | 31.0 | 82584 | 0.0277 | 0 | 1 |
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- | 0.0003 | 32.0 | 85248 | 0.0377 | 0 | 1 |
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- | 0.0003 | 33.0 | 87912 | 0.0354 | 0 | 1 |
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- | 0.0009 | 37.0 | 98568 | 0.0605 | 0 | 1 |
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- | 0.0002 | 38.0 | 101232 | 0.0613 | 0 | 1 |
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- | 0.0002 | 39.0 | 103896 | 0.0563 | 0 | 1 |
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- | 0.0002 | 40.0 | 106560 | 0.0632 | 0 | 1 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0102
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  - Mean Distance: 0
20
  - Max Distance: 1
21
 
 
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  The following hyperparameters were used during training:
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  - learning_rate: 0.0001
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+ - train_batch_size: 32
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+ - eval_batch_size: 32
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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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  - lr_scheduler_warmup_ratio: 0.1
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+ - num_epochs: 20
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Mean Distance | Max Distance |
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+ |:-------------:|:-----:|:-----:|:---------------:|:-------------:|:------------:|
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+ | 0.2779 | 1.0 | 1050 | 0.3371 | 0 | 1 |
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+ | 0.0346 | 2.0 | 2100 | 0.0173 | 0 | 1 |
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+ | 0.0072 | 3.0 | 3150 | 0.0077 | 0 | 1 |
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+ | 0.0057 | 4.0 | 4200 | 0.0093 | 0 | 1 |
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+ | 0.005 | 5.0 | 5250 | 0.0053 | 0 | 1 |
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+ | 0.002 | 6.0 | 6300 | 0.0056 | 0 | 1 |
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+ | 0.002 | 7.0 | 7350 | 0.0091 | 0 | 1 |
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+ | 0.0018 | 8.0 | 8400 | 0.0010 | 0 | 0 |
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+ | 0.0044 | 9.0 | 9450 | 0.0043 | 0 | 1 |
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+ | 0.0024 | 10.0 | 10500 | 0.0048 | 0 | 1 |
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+ | 0.0032 | 11.0 | 11550 | 0.0023 | 0 | 1 |
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+ | 0.0028 | 12.0 | 12600 | 0.0003 | 0 | 0 |
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+ | 0.0005 | 13.0 | 13650 | 0.0008 | 0 | 0 |
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+ | 0.0026 | 14.0 | 14700 | 0.0012 | 0 | 1 |
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+ | 0.0011 | 15.0 | 15750 | 0.0171 | 0 | 1 |
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+ | 0.0 | 16.0 | 16800 | 0.0120 | 0 | 1 |
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+ | 0.0001 | 17.0 | 17850 | 0.0031 | 0 | 1 |
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+ | 0.0007 | 18.0 | 18900 | 0.0165 | 0 | 1 |
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+ | 0.001 | 19.0 | 19950 | 0.0194 | 0 | 1 |
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+ | 0.0001 | 20.0 | 21000 | 0.0102 | 0 | 1 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
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