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mobilebert-uncased-biored-finetuned

Token Classification
Transformers
Safetensors
English
mobilebert
low-resource NER
token_classification
biomedicine
medical NER
Generated from Trainer
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Push google/mobilebert-uncased trained on biored-original_splits.pt (100 samples)

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  1. README.md +16 -24
  2. model.safetensors +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -28,12 +28,12 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [mobilebert-uncased](https://huggingface.co/mobilebert-uncased) on the bigbio/biored dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.7632
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- - Accuracy: 0.7385
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- - Precision: 0.2012
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- - Recall: 0.2384
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- - F1: 0.215
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- - Weighted F1: 0.7009
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  ## Model description
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@@ -64,24 +64,16 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Weighted F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:-----------:|
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- | No log | 1.0 | 25 | 1.2345 | 0.7114 | 0.1016 | 0.1429 | 0.1188 | 0.5914 |
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- | No log | 2.0 | 50 | 1.0379 | 0.7114 | 0.1016 | 0.1429 | 0.1188 | 0.5914 |
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- | No log | 3.0 | 75 | 1.0300 | 0.7114 | 0.1016 | 0.1429 | 0.1188 | 0.5914 |
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- | No log | 4.0 | 100 | 1.0228 | 0.7114 | 0.1016 | 0.1429 | 0.1188 | 0.5914 |
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- | No log | 5.0 | 125 | 1.0144 | 0.7114 | 0.1016 | 0.1429 | 0.1188 | 0.5914 |
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- | No log | 6.0 | 150 | 0.9994 | 0.7114 | 0.1016 | 0.1429 | 0.1188 | 0.5914 |
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- | No log | 7.0 | 175 | 0.9681 | 0.7114 | 0.1016 | 0.1429 | 0.1188 | 0.5914 |
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- | No log | 8.0 | 200 | 0.8869 | 0.7147 | 0.2167 | 0.1487 | 0.1303 | 0.6007 |
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- | No log | 9.0 | 225 | 0.8511 | 0.7242 | 0.2064 | 0.1716 | 0.1598 | 0.6298 |
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- | No log | 10.0 | 250 | 0.8187 | 0.7287 | 0.157 | 0.1991 | 0.1754 | 0.653 |
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- | No log | 11.0 | 275 | 0.8046 | 0.7317 | 0.1581 | 0.2035 | 0.1775 | 0.6581 |
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- | No log | 12.0 | 300 | 0.7900 | 0.732 | 0.1935 | 0.2126 | 0.1887 | 0.6688 |
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- | No log | 13.0 | 325 | 0.7865 | 0.734 | 0.2312 | 0.2129 | 0.1828 | 0.6664 |
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- | No log | 14.0 | 350 | 0.7758 | 0.7346 | 0.1604 | 0.2148 | 0.1819 | 0.6672 |
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- | No log | 15.0 | 375 | 0.7958 | 0.7376 | 0.2086 | 0.2141 | 0.1884 | 0.6697 |
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- | No log | 16.0 | 400 | 0.7757 | 0.733 | 0.2002 | 0.2347 | 0.2122 | 0.6904 |
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- | No log | 17.0 | 425 | 0.7874 | 0.7393 | 0.2067 | 0.2196 | 0.2119 | 0.6828 |
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- | No log | 18.0 | 450 | 0.7915 | 0.735 | 0.2043 | 0.2391 | 0.2197 | 0.6959 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [mobilebert-uncased](https://huggingface.co/mobilebert-uncased) on the bigbio/biored dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.0264
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+ - Accuracy: 0.7163
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+ - Precision: 0.1023
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+ - Recall: 0.1429
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+ - F1: 0.1192
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+ - Weighted F1: 0.5979
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Weighted F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:-----------:|
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+ | No log | 1.0 | 13 | 1.6911 | 0.7114 | 0.1016 | 0.1429 | 0.1188 | 0.5914 |
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+ | No log | 2.0 | 26 | 1.2080 | 0.7114 | 0.1016 | 0.1429 | 0.1188 | 0.5914 |
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+ | No log | 3.0 | 39 | 1.0905 | 0.7114 | 0.1016 | 0.1429 | 0.1188 | 0.5914 |
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+ | No log | 4.0 | 52 | 1.0400 | 0.7114 | 0.1016 | 0.1429 | 0.1188 | 0.5914 |
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+ | No log | 5.0 | 65 | 1.0439 | 0.7114 | 0.1016 | 0.1429 | 0.1188 | 0.5914 |
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+ | No log | 6.0 | 78 | 1.0288 | 0.7114 | 0.1016 | 0.1429 | 0.1188 | 0.5914 |
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+ | No log | 7.0 | 91 | 1.0259 | 0.7114 | 0.1016 | 0.1429 | 0.1188 | 0.5914 |
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+ | No log | 8.0 | 104 | 1.0180 | 0.7114 | 0.1016 | 0.1429 | 0.1188 | 0.5914 |
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+ | No log | 9.0 | 117 | 1.0229 | 0.7114 | 0.1016 | 0.1429 | 0.1188 | 0.5914 |
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+ | No log | 10.0 | 130 | 1.0186 | 0.7114 | 0.1016 | 0.1429 | 0.1188 | 0.5914 |
 
 
 
 
 
 
 
 
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  ### Framework versions
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