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modernbert-tr-classifier

Text Classification
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modernbert
Generated from Trainer
text-embeddings-inference
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End of training

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  1. README.md +23 -23
  2. model.safetensors +1 -1
  3. runs/Jan23_16-34-12_ultramarine/events.out.tfevents.1737639253.ultramarine.3988838.0 +2 -2
README.md CHANGED
@@ -19,9 +19,9 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [answerdotai/ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.8071
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- - F1: 0.7980
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- - Accuracy: 0.7959
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  ## Model description
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@@ -47,7 +47,7 @@ The following hyperparameters were used during training:
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  - gradient_accumulation_steps: 2
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  - total_train_batch_size: 256
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  - optimizer: Use adamw_torch with betas=(0.9,0.98) and epsilon=1e-06 and optimizer_args=No additional optimizer arguments
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- - lr_scheduler_type: cosine
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  - lr_scheduler_warmup_steps: 500
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  - num_epochs: 20
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@@ -55,25 +55,25 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | F1 | Accuracy |
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  |:-------------:|:-------:|:----:|:---------------:|:------:|:--------:|
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- | 3.981 | 1.0 | 19 | 1.9665 | 0.0904 | 0.1633 |
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- | 3.6781 | 2.0 | 38 | 1.8383 | 0.1882 | 0.2449 |
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- | 3.1283 | 3.0 | 57 | 1.4232 | 0.4896 | 0.5061 |
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- | 2.4044 | 4.0 | 76 | 1.2398 | 0.5488 | 0.5673 |
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- | 1.9166 | 5.0 | 95 | 1.1468 | 0.5726 | 0.6041 |
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- | 1.7122 | 6.0 | 114 | 1.0013 | 0.6649 | 0.6653 |
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- | 1.4626 | 7.0 | 133 | 0.8954 | 0.7198 | 0.7224 |
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- | 1.2173 | 8.0 | 152 | 0.7306 | 0.7611 | 0.7592 |
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- | 1.0648 | 9.0 | 171 | 0.7449 | 0.7412 | 0.7388 |
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- | 0.9008 | 10.0 | 190 | 0.6874 | 0.7754 | 0.7714 |
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- | 0.856 | 11.0 | 209 | 0.6584 | 0.8071 | 0.8082 |
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- | 0.7557 | 12.0 | 228 | 0.6046 | 0.7854 | 0.7837 |
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- | 0.472 | 13.0 | 247 | 0.8246 | 0.7428 | 0.7429 |
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- | 0.4386 | 14.0 | 266 | 0.7892 | 0.8042 | 0.8082 |
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- | 0.3418 | 15.0 | 285 | 0.6727 | 0.8248 | 0.8286 |
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- | 0.2662 | 16.0 | 304 | 0.8244 | 0.8144 | 0.8163 |
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- | 0.1774 | 17.0 | 323 | 0.7832 | 0.8083 | 0.8041 |
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- | 0.1246 | 18.0 | 342 | 0.5501 | 0.8703 | 0.8694 |
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- | 0.121 | 18.9730 | 360 | 0.8071 | 0.7980 | 0.7959 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [answerdotai/ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.8739
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+ - F1: 0.8061
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+ - Accuracy: 0.8082
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  ## Model description
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  - gradient_accumulation_steps: 2
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  - total_train_batch_size: 256
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  - optimizer: Use adamw_torch with betas=(0.9,0.98) and epsilon=1e-06 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: linear
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  - lr_scheduler_warmup_steps: 500
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  - num_epochs: 20
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  | Training Loss | Epoch | Step | Validation Loss | F1 | Accuracy |
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  |:-------------:|:-------:|:----:|:---------------:|:------:|:--------:|
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+ | 4.0021 | 1.0 | 19 | 1.9146 | 0.0636 | 0.1469 |
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+ | 3.6752 | 2.0 | 38 | 1.7785 | 0.3022 | 0.3388 |
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+ | 3.2521 | 3.0 | 57 | 1.4559 | 0.4311 | 0.4735 |
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+ | 2.6907 | 4.0 | 76 | 1.1927 | 0.5475 | 0.5714 |
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+ | 2.2003 | 5.0 | 95 | 0.9852 | 0.6614 | 0.6571 |
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+ | 1.7928 | 6.0 | 114 | 0.8017 | 0.7147 | 0.7102 |
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+ | 1.4909 | 7.0 | 133 | 0.8603 | 0.7070 | 0.7020 |
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+ | 1.3136 | 8.0 | 152 | 0.6970 | 0.7395 | 0.7429 |
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+ | 1.1483 | 9.0 | 171 | 0.5679 | 0.7774 | 0.7755 |
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+ | 0.903 | 10.0 | 190 | 0.9122 | 0.7078 | 0.7061 |
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+ | 0.886 | 11.0 | 209 | 0.6270 | 0.7707 | 0.7755 |
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+ | 0.7609 | 12.0 | 228 | 0.6756 | 0.8038 | 0.8082 |
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+ | 0.6929 | 13.0 | 247 | 0.5790 | 0.8290 | 0.8327 |
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+ | 0.4927 | 14.0 | 266 | 0.7072 | 0.8067 | 0.8082 |
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+ | 0.3282 | 15.0 | 285 | 0.6293 | 0.8490 | 0.8490 |
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+ | 0.2706 | 16.0 | 304 | 0.8920 | 0.7867 | 0.7878 |
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+ | 0.2311 | 17.0 | 323 | 0.7759 | 0.8466 | 0.8490 |
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+ | 0.1268 | 18.0 | 342 | 0.7496 | 0.8324 | 0.8327 |
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+ | 0.1276 | 18.9730 | 360 | 0.8739 | 0.8061 | 0.8082 |
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  ### Framework versions
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