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BonySmoke
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gec_uk_seq2tag

Token Classification
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roberta
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BonySmoke commited on
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Improve Spelling and Add Verb Voice

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  1. README.md +10 -10
  2. config.json +0 -0
  3. model.safetensors +2 -2
  4. runs/Nov09_16-50-22_872f85fd420c/events.out.tfevents.1699548634.872f85fd420c.154.0 +3 -0
  5. training_args.bin +1 -1
README.md CHANGED
@@ -19,11 +19,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [youscan/ukr-roberta-base](https://huggingface.co/youscan/ukr-roberta-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.7309
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- - Precision: 0.5140
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- - Recall: 0.2963
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- - F1: 0.3759
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- - Accuracy: 0.9215
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  ## Model description
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@@ -43,7 +43,7 @@ More information needed
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  The following hyperparameters were used during training:
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  - learning_rate: 2e-05
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- - train_batch_size: 2
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  - eval_batch_size: 4
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
@@ -52,10 +52,10 @@ The following hyperparameters were used during training:
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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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- | 0.4693 | 1.0 | 6484 | 0.7053 | 0.5110 | 0.2660 | 0.3499 | 0.9203 |
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- | 0.3783 | 2.0 | 12968 | 0.7309 | 0.5140 | 0.2963 | 0.3759 | 0.9215 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [youscan/ukr-roberta-base](https://huggingface.co/youscan/ukr-roberta-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.6727
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+ - Precision: 0.4979
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+ - Recall: 0.2675
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+ - F1: 0.3480
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+ - Accuracy: 0.9269
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 2e-05
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+ - train_batch_size: 4
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  - eval_batch_size: 4
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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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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | 0.4551 | 1.0 | 3242 | 0.6517 | 0.5123 | 0.2563 | 0.3417 | 0.9273 |
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+ | 0.3785 | 2.0 | 6484 | 0.6727 | 0.4979 | 0.2675 | 0.3480 | 0.9269 |
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  ### Framework versions
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