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datleviet
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ComOM-VIDeBERTa-3

Token Classification
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deberta-v2
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End of training

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  1. README.md +14 -11
  2. model.safetensors +1 -1
  3. runs/Dec05_11-41-41_122b6e7e2106/events.out.tfevents.1701776502.122b6e7e2106.47.3 +2 -2
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 [Fsoft-AIC/videberta-base](https://huggingface.co/Fsoft-AIC/videberta-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.2146
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- - Precision: 0.0644
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- - Recall: 0.0210
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- - F1: 0.0317
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- - Accuracy: 0.6473
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  ## Model description
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@@ -48,17 +48,20 @@ 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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- | No log | 1.0 | 78 | 1.3150 | 0.0260 | 0.0020 | 0.0037 | 0.6324 |
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- | No log | 2.0 | 156 | 1.2537 | 0.0602 | 0.0130 | 0.0214 | 0.6377 |
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- | No log | 3.0 | 234 | 1.2357 | 0.0524 | 0.0120 | 0.0195 | 0.6402 |
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- | No log | 4.0 | 312 | 1.2163 | 0.05 | 0.0160 | 0.0242 | 0.6455 |
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- | No log | 5.0 | 390 | 1.2146 | 0.0644 | 0.0210 | 0.0317 | 0.6473 |
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [Fsoft-AIC/videberta-base](https://huggingface.co/Fsoft-AIC/videberta-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.0971
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+ - Precision: 0.1319
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+ - Recall: 0.1029
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+ - F1: 0.1156
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+ - Accuracy: 0.6647
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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: 8
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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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+ | No log | 1.0 | 78 | 1.2306 | 0.0768 | 0.0370 | 0.0499 | 0.6486 |
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+ | No log | 2.0 | 156 | 1.1902 | 0.0755 | 0.0609 | 0.0674 | 0.6407 |
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+ | No log | 3.0 | 234 | 1.1627 | 0.0923 | 0.0679 | 0.0783 | 0.6499 |
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+ | No log | 4.0 | 312 | 1.1489 | 0.1159 | 0.0879 | 0.1000 | 0.6530 |
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+ | No log | 5.0 | 390 | 1.1219 | 0.0997 | 0.0749 | 0.0856 | 0.6529 |
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+ | No log | 6.0 | 468 | 1.1130 | 0.1245 | 0.0879 | 0.1030 | 0.6589 |
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+ | 1.0673 | 7.0 | 546 | 1.1095 | 0.1247 | 0.0919 | 0.1058 | 0.6600 |
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+ | 1.0673 | 8.0 | 624 | 1.0971 | 0.1319 | 0.1029 | 0.1156 | 0.6647 |
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  ### Framework versions
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