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dgalik
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emoBank_LaBSE_test1

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End of training

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  1. README.md +14 -6
  2. pytorch_model.bin +1 -1
README.md CHANGED
@@ -14,10 +14,10 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [old_models/LaBSE/0_Transformer](https://huggingface.co/old_models/LaBSE/0_Transformer) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 3.8454
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- - Mse V: 4.9577
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- - Mse A: 3.2391
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- - Mse D: 3.3394
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  ## Model description
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@@ -40,14 +40,22 @@ The following hyperparameters were used during training:
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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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- - gradient_accumulation_steps: 2
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- - total_train_batch_size: 64
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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: 8
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  ### Training results
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  ### Framework versions
 
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  This model is a fine-tuned version of [old_models/LaBSE/0_Transformer](https://huggingface.co/old_models/LaBSE/0_Transformer) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0464
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+ - Mse V: 0.0518
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+ - Mse A: 0.0486
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+ - Mse D: 0.0387
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  ## Model description
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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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  - num_epochs: 8
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Mse V | Mse A | Mse D |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|
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+ | No log | 1.0 | 252 | 0.0639 | 0.0783 | 0.0770 | 0.0364 |
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+ | 0.1799 | 2.0 | 504 | 0.0502 | 0.0610 | 0.0545 | 0.0350 |
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+ | 0.1799 | 3.0 | 756 | 0.0495 | 0.0497 | 0.0465 | 0.0524 |
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+ | 0.0606 | 4.0 | 1008 | 0.0504 | 0.0655 | 0.0449 | 0.0409 |
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+ | 0.0606 | 5.0 | 1260 | 0.0495 | 0.0649 | 0.0467 | 0.0369 |
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+ | 0.0473 | 6.0 | 1512 | 0.0461 | 0.0520 | 0.0470 | 0.0394 |
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+ | 0.0473 | 7.0 | 1764 | 0.0473 | 0.0517 | 0.0508 | 0.0395 |
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+ | 0.041 | 8.0 | 2016 | 0.0464 | 0.0518 | 0.0486 | 0.0387 |
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  ### Framework versions
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