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Pictalk_large

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LucasMagnana/Pictalk

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  1. README.md +52 -5
  2. model.safetensors +1 -1
  3. runs/Jan23_15-29-08_e2189d3addf8/events.out.tfevents.1706023749.e2189d3addf8.34673.0 +2 -2
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 [bert-large-uncased-whole-word-masking](https://huggingface.co/bert-large-uncased-whole-word-masking) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.5561
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  ## Model description
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@@ -40,16 +40,63 @@ 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: 3.0
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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 |
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  |:-------------:|:-----:|:----:|:---------------:|
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- | 0.5356 | 1.0 | 21 | 1.4643 |
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- | 0.5393 | 2.0 | 42 | 1.4886 |
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- | 0.518 | 3.0 | 63 | 1.5391 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [bert-large-uncased-whole-word-masking](https://huggingface.co/bert-large-uncased-whole-word-masking) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.5286
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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: 50
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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 |
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  |:-------------:|:-----:|:----:|:---------------:|
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+ | 3.2507 | 1.0 | 25 | 2.7433 |
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+ | 2.518 | 2.0 | 50 | 2.2772 |
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+ | 2.323 | 3.0 | 75 | 2.0185 |
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+ | 2.0883 | 4.0 | 100 | 1.9731 |
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+ | 1.8835 | 5.0 | 125 | 1.9086 |
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+ | 1.8641 | 6.0 | 150 | 1.7880 |
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+ | 1.7244 | 7.0 | 175 | 1.7763 |
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+ | 1.7395 | 8.0 | 200 | 1.7191 |
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+ | 1.6834 | 9.0 | 225 | 1.6734 |
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+ | 1.6631 | 10.0 | 250 | 1.6970 |
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+ | 1.5764 | 11.0 | 275 | 1.6939 |
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+ | 1.54 | 12.0 | 300 | 1.6576 |
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+ | 1.5205 | 13.0 | 325 | 1.5530 |
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+ | 1.4832 | 14.0 | 350 | 1.5448 |
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+ | 1.4582 | 15.0 | 375 | 1.6000 |
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+ | 1.418 | 16.0 | 400 | 1.5240 |
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+ | 1.4152 | 17.0 | 425 | 1.5330 |
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+ | 1.3529 | 18.0 | 450 | 1.5850 |
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+ | 1.3886 | 19.0 | 475 | 1.4814 |
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+ | 1.3268 | 20.0 | 500 | 1.6087 |
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+ | 1.2914 | 21.0 | 525 | 1.5714 |
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+ | 1.3431 | 22.0 | 550 | 1.4989 |
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+ | 1.2838 | 23.0 | 575 | 1.5934 |
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+ | 1.2943 | 24.0 | 600 | 1.4751 |
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+ | 1.2704 | 25.0 | 625 | 1.5158 |
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+ | 1.284 | 26.0 | 650 | 1.6148 |
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+ | 1.2148 | 27.0 | 675 | 1.4828 |
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+ | 1.2382 | 28.0 | 700 | 1.4890 |
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+ | 1.1684 | 29.0 | 725 | 1.5531 |
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+ | 1.2053 | 30.0 | 750 | 1.4755 |
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+ | 1.1973 | 31.0 | 775 | 1.4426 |
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+ | 1.2127 | 32.0 | 800 | 1.5464 |
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+ | 1.1802 | 33.0 | 825 | 1.4410 |
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+ | 1.1828 | 34.0 | 850 | 1.5026 |
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+ | 1.1338 | 35.0 | 875 | 1.5691 |
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+ | 1.11 | 36.0 | 900 | 1.5073 |
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+ | 1.1456 | 37.0 | 925 | 1.5055 |
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+ | 1.1253 | 38.0 | 950 | 1.5108 |
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+ | 1.1214 | 39.0 | 975 | 1.4563 |
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+ | 1.1654 | 40.0 | 1000 | 1.5881 |
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+ | 1.0921 | 41.0 | 1025 | 1.4060 |
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+ | 1.1087 | 42.0 | 1050 | 1.4952 |
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+ | 1.0824 | 43.0 | 1075 | 1.5512 |
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+ | 1.1127 | 44.0 | 1100 | 1.5481 |
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+ | 1.0994 | 45.0 | 1125 | 1.5692 |
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+ | 1.0579 | 46.0 | 1150 | 1.4802 |
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+ | 1.1006 | 47.0 | 1175 | 1.5585 |
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+ | 1.0692 | 48.0 | 1200 | 1.4303 |
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+ | 1.1131 | 49.0 | 1225 | 1.5129 |
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+ | 1.0943 | 50.0 | 1250 | 1.5286 |
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  ### Framework versions
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