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---
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-large
tags:
- generated_from_trainer
model-index:
- name: ModernBERT-large_massive_modernbert_large_crf_v1
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# ModernBERT-large_massive_modernbert_large_crf_v1
This model is a fine-tuned version of [answerdotai/ModernBERT-large](https://huggingface.co/answerdotai/ModernBERT-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 15.5718
- Slot P: 0.5398
- Slot R: 0.6408
- Slot F1: 0.5860
- Slot Exact Match: 0.6001
- Intent Acc: 0.7831
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 256
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.06
- num_epochs: 30
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Slot P | Slot R | Slot F1 | Slot Exact Match | Intent Acc |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:-------:|:----------------:|:----------:|
| No log | 1.0 | 45 | 43.3614 | 0.0 | 0.0 | 0.0 | 0.3178 | 0.0821 |
| 160.2669 | 2.0 | 90 | 27.2292 | 0.3143 | 0.2269 | 0.2635 | 0.3586 | 0.2548 |
| 66.654 | 3.0 | 135 | 19.2474 | 0.4379 | 0.4 | 0.4181 | 0.4481 | 0.4575 |
| 38.629 | 4.0 | 180 | 15.3625 | 0.4023 | 0.5408 | 0.4614 | 0.4801 | 0.5903 |
| 23.3498 | 5.0 | 225 | 12.4194 | 0.4446 | 0.5706 | 0.4998 | 0.5411 | 0.6695 |
| 12.7922 | 6.0 | 270 | 12.3227 | 0.5013 | 0.5980 | 0.5454 | 0.5691 | 0.6990 |
| 7.8613 | 7.0 | 315 | 12.8060 | 0.4926 | 0.6 | 0.5410 | 0.5642 | 0.7324 |
| 5.4037 | 8.0 | 360 | 12.9247 | 0.5086 | 0.6294 | 0.5626 | 0.5809 | 0.7388 |
| 3.6892 | 9.0 | 405 | 13.9871 | 0.5260 | 0.6343 | 0.5751 | 0.5986 | 0.7605 |
| 2.6797 | 10.0 | 450 | 14.0965 | 0.5562 | 0.6204 | 0.5865 | 0.6011 | 0.7742 |
| 2.6797 | 11.0 | 495 | 13.8520 | 0.5105 | 0.6398 | 0.5679 | 0.5775 | 0.7698 |
| 2.0031 | 12.0 | 540 | 15.0858 | 0.5491 | 0.6289 | 0.5863 | 0.6080 | 0.7698 |
| 1.3894 | 13.0 | 585 | 15.5718 | 0.5398 | 0.6408 | 0.5860 | 0.6001 | 0.7831 |
### Framework versions
- Transformers 4.55.0
- Pytorch 2.7.0+cu126
- Datasets 3.6.0
- Tokenizers 0.21.4
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