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silviacamplani
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distilbert-finetuned-dapt-ner-music

Token Classification
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silviacamplani commited on
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1 Parent(s): 05b2396

Training in progress epoch 3

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Files changed (4) hide show
  1. README.md +10 -7
  2. logs/train/events.out.tfevents.1661703305.3e81d4e42f0b.17.0.v2 +2 -2
  3. logs/validation/events.out.tfevents.1661703324.3e81d4e42f0b.17.1.v2 +2 -2
  4. tf_model.h5 +1 -1
README.md CHANGED
@@ -14,13 +14,13 @@ probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [silviacamplani/distilbert-finetuned-dapt-lm-ai](https://huggingface.co/silviacamplani/distilbert-finetuned-dapt-lm-ai) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Train Loss: 2.5668
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- - Validation Loss: 1.9780
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- - Train Precision: 0.0
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- - Train Recall: 0.0
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- - Train F1: 0.0
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- - Train Accuracy: 0.5482
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- - Epoch: 0
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  ## Model description
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@@ -47,6 +47,9 @@ The following hyperparameters were used during training:
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  | Train Loss | Validation Loss | Train Precision | Train Recall | Train F1 | Train Accuracy | Epoch |
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  |:----------:|:---------------:|:---------------:|:------------:|:--------:|:--------------:|:-----:|
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  | 2.5668 | 1.9780 | 0.0 | 0.0 | 0.0 | 0.5482 | 0 |
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [silviacamplani/distilbert-finetuned-dapt-lm-ai](https://huggingface.co/silviacamplani/distilbert-finetuned-dapt-lm-ai) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Train Loss: 1.0982
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+ - Validation Loss: 1.0637
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+ - Train Precision: 0.4716
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+ - Train Recall: 0.4635
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+ - Train F1: 0.4675
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+ - Train Accuracy: 0.7155
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+ - Epoch: 3
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  ## Model description
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  | Train Loss | Validation Loss | Train Precision | Train Recall | Train F1 | Train Accuracy | Epoch |
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  |:----------:|:---------------:|:---------------:|:------------:|:--------:|:--------------:|:-----:|
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  | 2.5668 | 1.9780 | 0.0 | 0.0 | 0.0 | 0.5482 | 0 |
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+ | 1.7189 | 1.4888 | 0.1152 | 0.0396 | 0.0589 | 0.5905 | 1 |
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+ | 1.3060 | 1.2236 | 0.3797 | 0.3564 | 0.3677 | 0.6839 | 2 |
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+ | 1.0982 | 1.0637 | 0.4716 | 0.4635 | 0.4675 | 0.7155 | 3 |
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  ### Framework versions
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