Add support for upper У and В. Also merge and split of не and на
Browse files- README.md +7 -21
- config.json +0 -0
- model.safetensors +2 -2
- runs/Nov19_12-22-20_e5e5e07855ce/events.out.tfevents.1700396541.e5e5e07855ce.530.0 +3 -0
- training_args.bin +1 -1
README.md
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@@ -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.
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- Precision: 0.
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- Recall: 0.
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- F1: 0.
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- Accuracy: 0.
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## Model description
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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The model was evaluated on the validation dataset provided in the [UNLP 2023 Shared Task in Grammatical Error Correction for Ukrainian](https://github.com/asivokon/unlp-2023-shared-task/tree/main)
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```
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=========== Span-Based Correction ============
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TP FP FN Prec Rec F0.5
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433 229 794 0.6541 0.3529 0.5587
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==============================================
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============ Span-Based Detection ============
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TP FP FN Prec Rec F0.5
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498 163 758 0.7534 0.3965 0.6385
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==============================================
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```
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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: 0.6385
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- Precision: 0.4995
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- Recall: 0.2672
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- F1: 0.3482
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- Accuracy: 0.9325
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## Model description
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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| 0.441 | 1.0 | 3242 | 0.6187 | 0.5088 | 0.2602 | 0.3443 | 0.9329 |
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| 0.3626 | 2.0 | 6484 | 0.6385 | 0.4995 | 0.2672 | 0.3482 | 0.9325 |
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### Framework versions
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config.json
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model.safetensors
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runs/Nov19_12-22-20_e5e5e07855ce/events.out.tfevents.1700396541.e5e5e07855ce.530.0
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training_args.bin
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