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Hartunka
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tiny_bert_rand_20_v2

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distilbert
Generated from Trainer
Eval Results (legacy)
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  1. README.md +9 -21
  2. model.safetensors +1 -1
README.md CHANGED
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  ---
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  tags:
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  - generated_from_trainer
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- datasets:
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- - Hartunka/processed_wikitext-103-raw-v1-rand-20
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  metrics:
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  - accuracy
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  model-index:
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  - name: tiny_bert_rand_20_v2
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- results:
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- - task:
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- name: Masked Language Modeling
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- type: fill-mask
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- dataset:
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- name: Hartunka/processed_wikitext-103-raw-v1-rand-20
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- type: Hartunka/processed_wikitext-103-raw-v1-rand-20
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- metrics:
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- - name: Accuracy
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- type: accuracy
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- value: 0.15242696502232017
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -25,10 +13,10 @@ should probably proofread and complete it, then remove this comment. -->
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  # tiny_bert_rand_20_v2
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- This model is a fine-tuned version of [](https://huggingface.co/) on the Hartunka/processed_wikitext-103-raw-v1-rand-20 dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 9.3009
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- - Accuracy: 0.1524
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-------:|:-----:|:---------------:|:--------:|
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- | 9.1042 | 4.1982 | 10000 | 9.2962 | 0.1514 |
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- | 8.718 | 8.3963 | 20000 | 9.3425 | 0.1525 |
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- | 8.1812 | 12.5945 | 30000 | 9.8460 | 0.1542 |
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- | 7.5418 | 16.7926 | 40000 | 10.5329 | 0.1516 |
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- | 7.0563 | 20.9908 | 50000 | 11.3351 | 0.1519 |
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  ### Framework versions
 
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  ---
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  tags:
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  - generated_from_trainer
 
 
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  metrics:
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  - accuracy
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  model-index:
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  - name: tiny_bert_rand_20_v2
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+ results: []
 
 
 
 
 
 
 
 
 
 
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
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  # tiny_bert_rand_20_v2
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+ This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 11.3958
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+ - Accuracy: 0.1511
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-------:|:-----:|:---------------:|:--------:|
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+ | 9.1024 | 4.1982 | 10000 | 9.2437 | 0.1507 |
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+ | 8.7308 | 8.3963 | 20000 | 9.4041 | 0.1523 |
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+ | 8.2147 | 12.5945 | 30000 | 9.9708 | 0.1540 |
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+ | 7.5753 | 16.7926 | 40000 | 10.7708 | 0.1510 |
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+ | 7.0936 | 20.9908 | 50000 | 11.3958 | 0.1511 |
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  ### Framework versions
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