---
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
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# 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