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distilbert-base-uncased-finetuned-squad

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  1. README.md +9 -14
  2. config.json +1 -1
  3. logs/train/events.out.tfevents.1651751173.matt-TRX40-AORUS-PRO-WIFI.37307.0.v2 +3 -0
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  20. logs/train/events.out.tfevents.1656610468.matt-TRX40-AORUS-PRO-WIFI.67392.1.v2 +3 -0
  21. logs/validation/events.out.tfevents.1656611308.matt-TRX40-AORUS-PRO-WIFI.67392.2.v2 +3 -0
  22. special_tokens_map.json +7 -1
  23. tf_model.h5 +1 -1
  24. tokenizer_config.json +14 -1
README.md CHANGED
@@ -14,13 +14,9 @@ probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Train Loss: 0.9581
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- - Train End Logits Sparse Categorical Accuracy: 0.7344
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- - Train Start Logits Sparse Categorical Accuracy: 0.6948
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- - Validation Loss: 1.1235
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- - Validation End Logits Sparse Categorical Accuracy: 0.7005
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- - Validation Start Logits Sparse Categorical Accuracy: 0.6644
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- - Epoch: 1
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  ## Model description
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@@ -44,15 +40,14 @@ The following hyperparameters were used during training:
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  ### Training results
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- | Train Loss | Train End Logits Sparse Categorical Accuracy | Train Start Logits Sparse Categorical Accuracy | Validation Loss | Validation End Logits Sparse Categorical Accuracy | Validation Start Logits Sparse Categorical Accuracy | Epoch |
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- |:----------:|:--------------------------------------------:|:----------------------------------------------:|:---------------:|:-------------------------------------------------:|:---------------------------------------------------:|:-----:|
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- | 1.4902 | 0.6126 | 0.5751 | 1.1502 | 0.6844 | 0.6561 | 0 |
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- | 0.9581 | 0.7344 | 0.6948 | 1.1235 | 0.7005 | 0.6644 | 1 |
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  ### Framework versions
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- - Transformers 4.19.0.dev0
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- - TensorFlow 2.8.0-rc0
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- - Datasets 2.1.1.dev0
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  - Tokenizers 0.11.0
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  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Train Loss: 1.5154
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+ - Validation Loss: 1.1532
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+ - Epoch: 0
 
 
 
 
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  ## Model description
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  ### Training results
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+ | Train Loss | Validation Loss | Epoch |
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+ |:----------:|:---------------:|:-----:|
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+ | 1.5154 | 1.1532 | 0 |
 
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  ### Framework versions
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+ - Transformers 4.21.0.dev0
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+ - TensorFlow 2.9.1
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+ - Datasets 2.3.3.dev0
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  - Tokenizers 0.11.0
config.json CHANGED
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  "seq_classif_dropout": 0.2,
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  "sinusoidal_pos_embds": false,
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  "tie_weights_": true,
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- "transformers_version": "4.19.0.dev0",
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  }
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  "seq_classif_dropout": 0.2,
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