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stulcrad
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CNEC_extended_xlm-roberta-large

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xlm-roberta
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  1. README.md +16 -14
  2. model.safetensors +1 -1
  3. runs/Feb26_14-08-21_n29/events.out.tfevents.1708952902.n29.22263.0 +2 -2
README.md CHANGED
@@ -25,16 +25,16 @@ model-index:
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  metrics:
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  - name: Precision
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  type: precision
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- value: 0.862624348649929
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  - name: Recall
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  type: recall
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- value: 0.9037220843672457
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  - name: F1
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  type: f1
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- value: 0.8826951042171596
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  - name: Accuracy
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  type: accuracy
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- value: 0.9778103044496487
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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
@@ -44,11 +44,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [FacebookAI/xlm-roberta-large](https://huggingface.co/FacebookAI/xlm-roberta-large) on the cnec dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1070
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- - Precision: 0.8626
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- - Recall: 0.9037
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- - F1: 0.8827
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- - Accuracy: 0.9778
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  ## Model description
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@@ -73,16 +73,18 @@ 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 | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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- | 0.3643 | 1.12 | 500 | 0.1506 | 0.7225 | 0.8452 | 0.7790 | 0.9628 |
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- | 0.1213 | 2.24 | 1000 | 0.1073 | 0.7944 | 0.8725 | 0.8316 | 0.9723 |
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- | 0.0783 | 3.36 | 1500 | 0.1024 | 0.8424 | 0.8938 | 0.8673 | 0.9763 |
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- | 0.0562 | 4.47 | 2000 | 0.1070 | 0.8626 | 0.9037 | 0.8827 | 0.9778 |
 
 
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  ### Framework versions
 
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  metrics:
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  - name: Precision
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  type: precision
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+ value: 0.8625413320736892
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  - name: Recall
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  type: recall
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+ value: 0.9062034739454095
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  - name: F1
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  type: f1
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+ value: 0.8838334946757018
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  - name: Accuracy
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  type: accuracy
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+ value: 0.9776053864168618
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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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  This model is a fine-tuned version of [FacebookAI/xlm-roberta-large](https://huggingface.co/FacebookAI/xlm-roberta-large) on the cnec dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.1207
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+ - Precision: 0.8625
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+ - Recall: 0.9062
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+ - F1: 0.8838
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+ - Accuracy: 0.9776
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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: 7
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | 0.2631 | 1.12 | 500 | 0.1266 | 0.7607 | 0.8660 | 0.8099 | 0.9688 |
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+ | 0.1089 | 2.24 | 1000 | 0.1050 | 0.8199 | 0.8854 | 0.8513 | 0.9743 |
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+ | 0.0719 | 3.36 | 1500 | 0.1008 | 0.8400 | 0.8913 | 0.8649 | 0.9768 |
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+ | 0.0512 | 4.47 | 2000 | 0.1027 | 0.8394 | 0.8923 | 0.8650 | 0.9775 |
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+ | 0.0381 | 5.59 | 2500 | 0.1169 | 0.8588 | 0.9027 | 0.8802 | 0.9777 |
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+ | 0.0265 | 6.71 | 3000 | 0.1207 | 0.8625 | 0.9062 | 0.8838 | 0.9776 |
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  ### Framework versions
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