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multi-dimensional-disability

Safetensors
bert
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  2. model.safetensors +1 -1
README.md CHANGED
@@ -20,11 +20,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [alex-miller/ODABert](https://huggingface.co/alex-miller/ODABert) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.7126
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- - Accuracy: 0.8881
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- - F1: 0.8100
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- - Precision: 0.7556
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- - Recall: 0.8728
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  ## Model description
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@@ -49,22 +49,27 @@ 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: 5
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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- | 0.962 | 1.0 | 437 | 0.9254 | 0.8485 | 0.7272 | 0.7161 | 0.7386 |
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- | 0.8959 | 2.0 | 874 | 0.8276 | 0.8762 | 0.7906 | 0.7354 | 0.8546 |
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- | 0.8419 | 3.0 | 1311 | 0.7560 | 0.8801 | 0.7925 | 0.7517 | 0.8379 |
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- | 0.7452 | 4.0 | 1748 | 0.7235 | 0.8856 | 0.8048 | 0.7540 | 0.8630 |
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- | 0.7234 | 5.0 | 2185 | 0.7126 | 0.8881 | 0.8100 | 0.7556 | 0.8728 |
 
 
 
 
 
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  ### Framework versions
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  - Transformers 4.38.2
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- - Pytorch 2.2.1+cu121
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  - Datasets 2.18.0
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  - Tokenizers 0.15.2
 
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  This model is a fine-tuned version of [alex-miller/ODABert](https://huggingface.co/alex-miller/ODABert) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.6084
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+ - Accuracy: 0.9116
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+ - F1: 0.8471
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+ - Precision: 0.8029
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+ - Recall: 0.8966
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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: 10
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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+ | 0.9604 | 1.0 | 437 | 0.9473 | 0.8617 | 0.7483 | 0.7446 | 0.7519 |
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+ | 0.8897 | 2.0 | 874 | 0.8169 | 0.8804 | 0.7995 | 0.7380 | 0.8721 |
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+ | 0.8054 | 3.0 | 1311 | 0.7170 | 0.8858 | 0.8028 | 0.7601 | 0.8505 |
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+ | 0.6757 | 4.0 | 1748 | 0.6679 | 0.8921 | 0.8164 | 0.7631 | 0.8777 |
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+ | 0.6153 | 5.0 | 2185 | 0.6279 | 0.8992 | 0.8275 | 0.7772 | 0.8847 |
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+ | 0.5782 | 6.0 | 2622 | 0.5773 | 0.8995 | 0.8305 | 0.7705 | 0.9008 |
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+ | 0.5435 | 7.0 | 3059 | 0.6106 | 0.9072 | 0.8401 | 0.7937 | 0.8924 |
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+ | 0.5333 | 8.0 | 3496 | 0.6141 | 0.9079 | 0.8435 | 0.7878 | 0.9078 |
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+ | 0.5349 | 9.0 | 3933 | 0.6056 | 0.9097 | 0.8448 | 0.7964 | 0.8994 |
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+ | 0.539 | 10.0 | 4370 | 0.6084 | 0.9116 | 0.8471 | 0.8029 | 0.8966 |
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  ### Framework versions
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  - Transformers 4.38.2
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+ - Pytorch 2.4.1+cu121
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  - Datasets 2.18.0
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  - Tokenizers 0.15.2
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