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xlmr-lstm-crf-resume-ner

Token Classification
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xlm-roberta
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  1. README.md +1 -40
  2. model.safetensors +1 -1
  3. runs/Nov19_17-25-32_d1be6ed5b3f3/events.out.tfevents.1700422054.d1be6ed5b3f3.6890.1 +3 -0
  4. runs/Nov19_19-34-17_d1be6ed5b3f3/events.out.tfevents.1700422460.d1be6ed5b3f3.6890.2 +3 -0
  5. training_args.bin +2 -2
README.md CHANGED
@@ -3,11 +3,6 @@ license: mit
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  base_model: xlm-roberta-base
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  tags:
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  - generated_from_trainer
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- metrics:
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- - precision
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- - recall
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- - f1
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- - accuracy
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  model-index:
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  - name: xlmr-lstm-crf-resume-ner
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  results: []
@@ -19,12 +14,6 @@ should probably proofread and complete it, then remove this comment. -->
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  # xlmr-lstm-crf-resume-ner
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  This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset.
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- It achieves the following results on the evaluation set:
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- - Loss: 26.2892
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- - Precision: 0.8714
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- - Recall: 0.8971
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- - F1: 0.8841
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- - Accuracy: 0.9398
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  ## Model description
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@@ -50,35 +39,7 @@ The following hyperparameters were used during training:
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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: 100
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-
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- ### Training results
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-
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- | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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- |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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- | 82.4955 | 0.11 | 100 | 57.1952 | 0.0 | 0.0 | 0.0 | 0.7590 |
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- | 58.2029 | 0.22 | 200 | 47.6007 | 0.9412 | 0.4706 | 0.6275 | 0.8253 |
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- | 44.4656 | 0.33 | 300 | 41.2301 | 0.7674 | 0.4853 | 0.5946 | 0.8283 |
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- | 38.3105 | 0.44 | 400 | 34.7889 | 0.6140 | 0.5147 | 0.5600 | 0.8464 |
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- | 33.1407 | 0.55 | 500 | 32.4219 | 0.5 | 0.5294 | 0.5143 | 0.8735 |
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- | 29.2323 | 0.66 | 600 | 29.6968 | 0.6780 | 0.5882 | 0.6299 | 0.8825 |
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- | 27.7611 | 0.77 | 700 | 29.1259 | 0.65 | 0.5735 | 0.6094 | 0.8780 |
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- | 25.626 | 0.88 | 800 | 27.6424 | 0.6027 | 0.6471 | 0.6241 | 0.8901 |
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- | 22.9444 | 0.99 | 900 | 26.4424 | 0.7424 | 0.7206 | 0.7313 | 0.9066 |
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- | 23.0567 | 1.1 | 1000 | 26.6253 | 0.8033 | 0.7206 | 0.7597 | 0.9021 |
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- | 18.3865 | 1.21 | 1100 | 26.5443 | 0.8060 | 0.7941 | 0.8 | 0.9307 |
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- | 20.5945 | 1.32 | 1200 | 25.1565 | 0.9 | 0.7941 | 0.8438 | 0.9247 |
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- | 20.0981 | 1.43 | 1300 | 25.7204 | 0.7917 | 0.8382 | 0.8143 | 0.9413 |
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- | 17.4745 | 1.54 | 1400 | 25.5618 | 0.7568 | 0.8235 | 0.7887 | 0.9473 |
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- | 18.2305 | 1.64 | 1500 | 24.7287 | 0.7397 | 0.7941 | 0.7660 | 0.9398 |
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- | 17.8145 | 1.75 | 1600 | 25.8965 | 0.8056 | 0.8529 | 0.8286 | 0.9488 |
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- | 16.4689 | 1.86 | 1700 | 25.3026 | 0.8824 | 0.8824 | 0.8824 | 0.9729 |
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- | 15.3847 | 1.97 | 1800 | 24.7269 | 0.8507 | 0.8382 | 0.8444 | 0.9578 |
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- | 13.6318 | 2.08 | 1900 | 24.8136 | 0.8592 | 0.8971 | 0.8777 | 0.9473 |
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- | 13.4369 | 2.19 | 2000 | 26.2700 | 0.8841 | 0.8971 | 0.8905 | 0.9608 |
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- | 13.7298 | 2.3 | 2100 | 24.8570 | 0.8472 | 0.8971 | 0.8714 | 0.9518 |
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- | 13.0787 | 2.41 | 2200 | 25.9105 | 0.8696 | 0.8824 | 0.8759 | 0.9428 |
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- | 13.1534 | 2.52 | 2300 | 26.2892 | 0.8714 | 0.8971 | 0.8841 | 0.9398 |
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-
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  ### Framework versions
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  base_model: xlm-roberta-base
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  tags:
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  - generated_from_trainer
 
 
 
 
 
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  model-index:
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  - name: xlmr-lstm-crf-resume-ner
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  results: []
 
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  # xlmr-lstm-crf-resume-ner
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  This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset.
 
 
 
 
 
 
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  ## Model description
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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: 100
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+ - mixed_precision_training: Native AMP
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
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